• Rodney Dietert (2016) [1] The Human Superorganism: How the Microbiome Is Revolutionizing the Pursuit of a Healthy Life

• Marty Makary (2024) [2]
  Blind Spots: When Medicine Gets It Wrong, and What It Means for Our Health

• Forrest Maready (2025) [3]
  The Germ in the Dairy Pail: The 200-Year War on the World’s Most Amazing Food-Milk.

One brief perspective of their intersecting visions for transforming public health in the 21st century· follows, with later expansion.

Dietert (2016):

• replace highly processed foods with nutritionally dense, microbially rich whole foods;

• ‘seed and feed’ the gut microbiota;

• reverse epidemic of noncommunicable disease

· Makary (2024):

• recognize ‘blind spots’ (entrenched dogmas) that compromise public health, as
  the assumption of no ‘downside’ to antibiotics … except ‘carpetbombing the microbiota’;

• embrace conflicting evidence rather than suppress evidence for building trust

· Maready(2025):

• root causes of ‘milk problem’ included industrialization of dairy production,
  adulteration of ‘city milk’ (swill milk), fear and sensationalism of ‘war on microbes’, and
  unscrupulous promotion of artificial infant formula starting in the 1870s;

• ADULTERATED milk IS inherently dangerous, particularly for infants; physicians and scientists challenging dogma silenced;

• demonstrated benefits of high quality raw milk produced using stringent standards for
  pastured cows (as Certified Milk Program, 1893 onwards, commercial scale ~25,000 gallons daily by 1908), standards comparable to Raw Milk Institute (2011 to present)

• certified raw milk diet from pastured cows reduced infant mortality (1905 reference), reduced digestive disturbances compared to pasteurized milk (1909 reference), only effective treatment promoting recovery from chronic debilitating diseases, including colitis and tuberculosis (e.g., John D. Rockefeller, Upton Sinclair; 1910 reference)

To expand, The Human Superorganism was described by a book reviewer in 2016 as ‘fascinating, authoritative, and revolutionary,’ but the work is truely remarkable in its readability and veracity even in this past decade of unimagined advances in knowlege that microbes contribute to health. Author Rodney Dietert, a Cornell University Emeritus Professor, described Homo sapiens as a superorganism or holobiont, existing as a ‘mostly microbial’ hybrid, a conglomerate, an ecosystem, a powerful ecological network of multiple species. Even though plants and animals and microbes were assigned Genus and species names as single, complete entities, now they are understood to be superorganisms. Animals and plants not only co-exist with their microbial partners, but are ‘incomplete’ without them. Mutually beneficial and synergistic interactions maintain superorganism health. When key components of the ecosystem are missing or disturbed or replaced, superorganism health can be compromised transiently or long-term.

 Dietert proposed ‘paradigm-shifting arguments’ in his 2016 book and his later writings that challenge two fundamental beliefs or dogmas largely based in 19th century science: 1) ‘Humans are better off as pure organisms free of foreign microbes’; and 2) ‘the human genome is the key to future medical advances’. In essence, the microbiota revolution of the 21st century revealed Homo sapiens as incomplete without its microbiota, its microbial partners in health [4,5].

 Consider how overemphasis of germ theory from the 19th century has been ‘weaponized’, with increasing industrialization and consolidation of agriculture continuing into this decade, promoting microbially impoverished, highly-processed, nutrient-poor foods for an increasingly unhealthy population overcome with inflammatory and metabolic diseases. Ancient nutrient-dense foods (including milk complete with its natural microbiota that have supported human health for over ten millennia) have largely been replaced with highly processed foods in the typical US diet, to the detriment of public health. Dietert’s book called for a ‘revolution in public health’ that begins with a return to a diet dominated by nutrient dense, microbially rich whole foods to reverse the epidemic of non-communicable disease and begin building and sustaining diverse and resilient microbial partners that can withstand challenges by pathogens and other stressors.

Professor Dietert expanded his work on interactions of human superorganisms in a series of manuscripts in diverse journals, including Nourishing the Human Holobiont to Reduce the Risk of Non-Communicable Dieases: A Cow’s Milk Evidence Map Example in 2022. Highlights from that work follow.

• benefits AND risks exist for BOTH raw and pasteurized milks;

• downsides of pasteurizing are loss of benefits of bioactive components in milk, including microbiota, and loss of protection against allergy, asthma, respiratory diseases, and the world’s number one cause of human death, non-communicable diseases;

• outdated dogmas problematic for regulating 21st century raw milks 

 Dietert’s body of work intersects with that of Dr. Marty Makary, a physician and Commissioner of the Food and Drug Administration and author of Blind Spots [2]. In particular, Makary’s Chapter 3 describes the medical community’s ‘blind spot’ or dogma that there was no ‘downside’ to antibiotics … except ‘carpet-bombing the microbiota’. Consider also the common belief or dogma in the media and among some scientists that there is no ‘downside’ to pasteurizing (carpet-bombing) the milk microbiota.

 Similarly, both books by Makary and Forrest Maready emphasized patterns of clashes of culture with science. Medical and public health communities were complicit in suppression of scientific evidence conflicting with established and entrenched dogma. One ‘key’ example in both books is decades of suppression of evidence falsifying Ancel Key’s ‘lipid hypothesis’ unfortunately marketed as ‘fact’ that drove distorted government policies, now acknowledged as harmful to public health, despite dissent.

 The extensive historical research that Maready documents in The Germ in the Dairy Pail [3] points to converging crises related to milk in 1860s and beyond:  

i)                    industrialization of dairy production with confinement of malnourished urban cows more susceptible to overcrowding diseases and motivating adulteration of ‘swill milk’;

ii)                  overcrowding of urban humans lacking clean water, sanitation, and unadulterated nutritious foods;

iii)                sensationalism of the war on microbes, fueling a culture of germophobia and fear of milk microbes; and

iv)                aggressive and unscrupulous marketing of artificial infant formula in the late 1870s and onward as superior to raw milks, ‘purported to replicate mother’s milk through scientific formulation’.

In his book, Maready describes in many short chapters a long history of milk pasteurization mandates focused primarily on the 19th and 20th centuries. His perspective is that mandates were based on fear and economics, not scientific evidence of public health benefits and risks. Unfortunately, then as now, Maready noted that dissenting views of physicians and researchers were ignored in the strongly pro-pasteurization culture, much as Dr. Makary [2] noted suppression of warnings about the downsides of antibiotics in the medical community. A 21st -century risk analyst would likely attribute pro-pasteurization policies as based on ‘risk perceptions’, not risk estimates based on the available evidence for benefits and harms.

Maready’s research into early writings on the 200-year war on milk point to a ‘blind spot’ still masked in the 21st century:  pasteurization of milk began as a ‘convenient technological solution to industrialization’ of dairy practices in 19th century distilleries in NY City and other urban centers. Further, pasteurization was promoted by decades of decisions that appeared to put economics and politics before public health and animal health. Maready points out the ‘downsides’ of pasteurization: loss of benefit to humans, cows, and pasture-based dairies.

 Substantial evidence from historical documents and the work of medical professionals in the 19th and 20th centuries that the ‘milk problem’ was caused by 19th century adulterated milk (‘swill milk’) from unhealthy diseased confined cows fed malnutritious distillery waste, diluted with contaminated water to stretch profits, and amended with whitening agents (chalk, plaster of Paris, flour) to mask off colors. ‘Swill milk’ was ‘inherently dangerous’. Maready emphasizes the misconception or deception that ‘country milk’ or raw milk from healthy pastured cows was ‘inherently dangerous’.

 Pro-pasteurization regulations ignored production risks in favor of an endproduct kill-step (pasteurization), with losses in nutritional, developmental, and immunological benefits to both humans and cows. Industrial production (concentrated confined herds fed predominantly grains) and processing of milk (primarily pasteurization and homogenization) destroy the inherently beneficial nature of the milk microbiota and its ‘inimitable plethora’ of bioactive components that promote growth and development of healthy gut, respiratory, and neural systems while protecting against acute infectious and chronic non-communicable diseases. In addition to the references provided by Maready, check out these recent studies [6–11].

 Public fear, media sensationalism, and government overreach in the 19th and 20th centuries set the stage for today’s challenges to food freedom (1, p 136). Government responses often missed the mark, failing to address the root causes of tuberculosis and mortality (industrialized processes, overcrowding, poor nutrition and sanitation, inadequate human and veterinary health care) and instead imposed mandatory pasteurization of milk rather than improving and monitoring urban production practices (1, p 146).

 Maready described the Certified Milk Program founded by Dr. Henry Coit in 1892 and the intellectual and political climate that silenced dissenting medical views that revealed ‘downsides’ to pasteurization. Noted below are 13 bullets emphasizing remarkably fortelling quotes from physicians and scientists of the 19th and early 20th centuries that resonate with deeper 21st century knowledge from recent studies of the mammalian milk microbiota and its benefits and risks. They also resonate with the ‘pro-pasteurization blind spot’ that there is no ‘downside’ to pasteurizing milk (other than carpet-bombing the milk microbiota and other bioactive, thermally sensitive components of milk).

         i.            In the 1860s, the invention of microscopes that revealed microbes in milk provided a new lens to view food. Rural dairy farmers viewed raw milk from traditional grass-fed operations as needing no remediation [pasteurization] that masked quality issues of urban milk from confined cows and extend marketability of ‘city milk’ or ‘swill milk’. Yet, traditional farms were subject to unfair and burdensome regulations that addressed problems endemic to urban production systems.

Public discourse from physicians in this period included statements consistent with rural dairy farmers’ perspective:  ‘health regulation mistakenly conflates pure farm-produced [raw] milk with contaminated [adulterated] ‘swill milk’, unjustly burdening rural producers’; and ‘Heat sufficient to destroy all living organisms must necessarily alter the vital qualities of the milk itself. We risk eliminating both the harmful and the beneficial, with consequences we cannot yet predict.’ (1, p 107).

Then as now, regulatory overreach continues, as does the common misconception [misinformation or disinformation] that raw milk is ‘inherently dangerous’ rather than ‘made dangerous by recent industrial practices producing it’ (1, p 107).

The fundamental irony was unacknowledged in this period: rather than address ‘root cause’ of contamination (industrialized production practices, overcrowding, confinement, unnatural diets and adulteration), society embraced technological fixes that treated symptoms, perpetuating underlying problems (1, p 108).

       ii.            In 1878-1879, researchers Dr. Franz Soxlet and Claude Bernard noted that: ‘heating milk beyond 60° C (140° F) significantly impairs its enzyme content, altering its digestive properties’; ‘alternations from heat may profoundly affect nutritional properties of [milk’s] natural substances, compromising their physiological benefits’; ‘infants fed heated milk exhibited signs of malnutrition’; and raw milk promoted weight gain and development in laboratory animals over pasteurized milk (1, p 110-111).

     iii.            In 1893, NJ physician Dr. Henry L. Coit stated that the ‘certification of milk by medical commissions [Certified Milk Program] offers the best solution to our milk problem. Not through heat, which destroys vital elements, but through cleanliness and careful monitoring’ (1, p 138). Certification required compliance with stringent requirements for pastured cows, including tuberculosis testing, regular veterinary and worker inspections, rapid cooling, and microbial standards for bacterial indicators of proper hygienic processes (1, pp 138-139).

     iv.            In 1896, microbiologist Dr. Theobald Smith stated to the American Public Health Association: ‘Milk is not inherently dangerous. It is the disease borne within it, transmissible from infected cows to humans, that constitutes the real threat. Proper testing and segregation of diseased animals can restore milk’s status as a safe and wholesome food’. Maready notes that Dr. Smith’s voice was drowned out by commercial interests (pasteurization equipment manufacturers, infant formula producers, large urban dairy/distillery operations) and sensationalism in the media generating fear and vilification of milk (1, p 148).

       v.            In 1905, director of the Hygienic Laboratory of the Public Health Service Dr. Milton Rosenau noted that the Certified Milk Program ‘constitutes one of the most practical demonstrations in preventive medicine, illustrating the high sanitary standard attainable’, evidenced by reduced infant mortality (1, p 155). Further, Florida physician Dr. Charles Sanford Porter reported in a medical journal ‘the complete recovery of patients [at his sanitarium] suffering from chronic dyspepsia, colitis, and even tuberculosis through this regimen [certified raw milk diet]’ (1, p157).

     vi.            In 1906, physician-in-chief at NY Babies Hospital Dr. Emmett Holt warned that artificial infant formula was ‘inferior to natural methods [breastfeeding, wetnursing]. We must be cautious about embracing industrial solutions [artificial infant formula] without fully understanding their long-term consequences (1, pp 158-159).

Multiple studies demonstrate statistically significant loss of benefits of the ‘inimitable plethora’ of bioactives in raw milk [9,12] for infants fed pasteurized donor milk or artificial infant formulas [13].

   vii.            In 1907, a colleague of Louis Pasteur’s at the Pasteur Institute, Nobel laureate Elie Metchnikoff, wrote ‘the intestinal flora [microbiota] exerts a profound influence on our well-being that has been entirely overlooked,’ reflecting a profound shift towards a more nuanced and holistic perspective on germ theory (1, p 156).

Maready points readers to Pasteur’s obituary in 1895 that highlighted his contributions to germ theory but omitted milk pasteurization as a significant contribution to science. Maready laments that Pasteur, whose career was devoted to advancing understanding of fermentation and microbial life, was ten years later associated with indiscriminately sterilizing microbes in milk (1, p 163).

Scientists in the 21st century continue to follow Metchnikoff’s work, revisiting germ theory and the need for a paradigm shift towards a microbial theory of health that does not center on pathogens as ‘germs’ that will kill us (culture of germophobia) but incorporates beneficial microbes and host-microbiota-pathogen effects [14,15].

 viii.            In 1907, NJ physician Dr. Henry Coit testified that the proposed Chicago ordinance mandating pasteurization of milk was a rejection of a ‘proven solution [Certified Milk Programs] in favor of an industrial process that fundamentally alters a natural food. Certification addresses the source of contamination rather than attempting to correct it after the fact’ (1, pp 157-158).

     ix.            By 1908, despite higher production costs for certified milk, certified dairies operating at commercial scale in many US cities produced ~25,000 gallons daily for a ‘growing clientele of physicians, hospitals, and health-conscious families’ (1, p 156).

Clearly, the assumption that all raw milk was ‘inherently dangerous’ was unfounded in 1908, yet this assumption continues well into 2025. The words of risk analysis that apply are consistent NOT with ‘risk’ estimated using established frameworks and evidence-based models, but ‘risk perception’ based on

       x.            In 1909, Cornell Medical College physician Dr. Joseph Winters reported that ‘infants fed raw certified milk [from pastured cows] gained weight more rapidly and suffered fewer digestive disturbances than those receiving pasteurized milk (1, p 159).

·This statement is consistent with multiple studies demonstrating that benefits are lost when infants are fed pasteurized donor breastmilk rather than raw donor breastmilk or mother’s own milk [6,16–20].

     xi.            In 1910, two eminent citizens embraced the certified raw milk diet, 70-year old oil magnate John D. Rockefeller in Cleveland and writer Upton Sinclair (The Jungle, 1905-1906; The Raw Food Table, 1911) in NY City. Both had suffered chronic debilitating digestive disease and fatigue that had not responded to medical treatments until certified raw milk diet was prescribed.

   xii.            In 1912, Dr. Charles North, cofounder of the American Association of Medical Milk Commissions or AAMMC, lamented abandonment of proven preventative approach of production using the Certified Milk Program, in favor of pasteurization, indiscriminately killing all bacteria. In reality, this policy did not arise from scientific progress, but ‘industrial convenience masquerading as public health’ protection (1, p 158).

 xiii.            In 1921, Columbia University’s Dr. Alfred Hess wrote that the ‘biological relationship between nutrition and health suggests that we must reconsider overly simplistic views of microbes [as germs that will kill us], understanding their potential to contribute positively to human physiology’ (1, p 160). The nuanced reality of milkborne microbes with beneficial or harmful effects was not understood then or now. ‘Microbes were feared as monstrous deadly invaders, and sensationalism in a culture of germophobia seems to outpace scientific understanding’ (1, p 102).

These statements are consistent with Cornell Emeritus Professor Rodney Dietert’s understanding that microbes in our diet and in our bodies are actually more likely to be our partners in health [1,4,5,21,22].

Beginning in the 1880s, voices of dissent, including well-respected medical professionals and scientists and John D. Rockefeller, Upton Sinclair, and others who benefitted from the certified raw milk diet, recognized the distinction between milk produced by healthy pastured cows and that produced by confined diseased cows fed unnatural diets. Currently, informed consumers and the Raw Milk Institute (https://www.rawmilkinstitute.org/updates/two-types-of-raw-milk) recognize these two distinct types of milk, one produced for direct human consumption as raw milk, the other ‘pre-pasteurized milk’ NOT produced according to farmer training, guidelines, and common standards essential for safe high quality milk compete with its natural microbiota (https://www.rawmilkinstitute.org/common-standards).

The root cause of milkborne disease in the !9th and 20th centuries was not the inherent nature of raw milk from well-managed pastured herds, but the adulterated nature of raw milk from stressed animals produced by industrialized processes in confinement and abuse. As Maready points out, ‘science has evolved, but policy has not caught up ([1], p 213).

Deliberation of past and current evidence is merited regarding the revealing truths about the Medical Milk Commissions that oversaw Certified Raw Milk Programs [23–25] that produced safe and wholesome raw milk from pastured cows for decades. The current training, guidelines, and standards provided by the Raw Milk Institute (https://www.rawmilkinstitute.org/about-raw-milk) are consistent with most aspects of the Certified Milk Programs.

References

1.           Dietert, R. The Human Superorganism: How the Microbiome Is Revolutionizing the Pursuit of a Healthy Life; Dutton: New York, New York, 2016;

2.           Makary, M. Blind Spots: When Medicine Gets It Wrong and What It Means for Our Health; Bloomsbury Publishing, 2024;

3.           Maready, F. The Germ in the Dairy Pail: The 200-Year War on the World’s Most Amazing Food-Milk; Feels Like Fire: Wilmington, NC USA, 2025;

4.           Dietert, R.R. A Focus on Microbiome Completeness and Optimized Colonization Resistance in Neonatology. Neoreviews 2018, 19, e78–e88, doi:10.1542/neo.19-2-e78.

5.           Dietert, R.R.; Dietert, J.M. Twentieth Century Dogmas Prevent Sustainable Healthcare. Am J Biomed Sci Res 2021, 13, 409–417, doi:10.34297/AJBSR.2021.13.001890.

6.           Coleman, M.E.; Dietert, R.R.; North, D.W. Recent Evidence for Benefit-Risk Analysis of the Breastmilk Ecosystem 2021.

7.           Coleman, M.E.; North, D.W. Revisioning Small Family Dairy Farms That Apply One Health Approaches. 2023, 5.

8.           Dietert, R.R.; Coleman, M.E.; North, D.W.; Stephenson, M.M. Nourishing the Human Holobiont to Reduce the Risk of Non-Communicable Diseases: A Cow’s Milk Evidence Map Example. Applied Microbiology 2022, 2, 25–52, doi:10.3390/applmicrobiol2010003.

9.           Fernández, L.; Ruiz, L.; Jara, J.; Orgaz, B.; Rodríguez, J.M. Strategies for the Preservation, Restoration and Modulation of the Human Milk Microbiota. Implications for Human Milk Banks and Neonatal Intensive Care Units. Frontiers in Microbiology 2018, 9, 2676.

10.        Gallo, V.; Arienzo, A.; Tomassetti, F.; Antonini, G. Milk Bioactive Compounds and Gut Microbiota Modulation: The Role of Whey Proteins and Milk Oligosaccharides. Foods 2024, 13, 907, doi:10.3390/foods13060907.

11.        Stephenson, M.M.; Coleman, M.E.; Azzolina, N.A. Trends in Burdens of Disease by Transmission Source (USA, 2005–2020) and Hazard Identification for Foods: Focus on Milkborne Disease. J Epidemiol Glob Health 2024, doi:10.1007/s44197-024-00216-6.

12.        Coleman, M.E. Deliberating the Scientific Evidence Base for Influenza Transmission to Raw Milk Consumers. Risk Analysis 2025, doi:https://doi.org/10.1111/risa.70077.

13.        Coleman, M.E.; North, D.W.; Dietert, R.R.; Stephenson, M.M. Examining Evidence of Benefits and Risks for Pasteurizing Donor Breastmilk. Applied Microbiology 2021, 1, 408–425, doi:10.3390/applmicrobiol1030027.

14.        Scott, E.A.; Bruning, E.; Nims, R.W.; Rubino, J.R.; Ijaz, M.K. A 21st Century View of Infection Control in Everyday Settings: Moving from the Germ Theory of Disease to the Microbial Theory of Health. American Journal of Infection Control 2020, 48, 1387–1392, doi:10.1016/j.ajic.2020.05.012.

15.        Carlsson, F.; Råberg, L. The Germ Theory Revisited: A Noncentric View on Infection Outcome. Proceedings of the National Academy of Sciences 2024, 121, e2319605121, doi:10.1073/pnas.2319605121.

16.        Briere, C.-E.; Gomez, J. Fresh Parent’s Own Milk for Preterm Infants: Barriers and Future Opportunities. Nutrients 2024, 16, 362, doi:10.3390/nu16030362.

17.        Chen, J.; Wesemael, A.J. van; Denswil, N.P.; Niemarkt, H.J.; Goudoever, J.B. van; Muncan, V.; Meij, T.G.J. de; Akker, C.H.P. van den Impact of Mother’s Own Milk vs. Donor Human Milk on Gut Microbiota Colonization in Preterm Infants: A Systematic Review. mrr 2024, 4, N/A-N/A, doi:10.20517/mrr.2024.44.

18.        Dombrowska-Pali, A.; Wiktorczyk-Kapischke, N.; Chrustek, A.; Olszewska-Słonina, D.; Gospodarek-Komkowska, E.; Socha, M.W. Human Milk Microbiome-A Review of Scientific Reports. Nutrients 2024, 16, 1420, doi:10.3390/nu16101420.

19.        Lund, A.-M.; Löfqvist, C.; Pivodic, A.; Lundgren, P.; Hård, A.-L.; Hellström, A.; Hansen-Pupp, I. Unpasteurised Maternal Breast Milk Is Positively Associated with Growth Outcomes in Extremely Preterm Infants. Acta Paediatrica 2020, 109, 1138–1147, doi:10.1111/apa.15102.

20.        Pütz, E.; Ascherl, R.; Wendt, T.; Thome, U.H.; Gebauer, C.; Genuneit, J.; Siziba, L.P. The Association of Different Types of Human Milk with Bronchopulmonary Dysplasia in Preterm Infants. Front. Nutr. 2024, 11, doi:10.3389/fnut.2024.1408033.

21.        Dietert, R.R. Safety and Risk Assessment for the Human Superorganism. Human and Ecological Risk Assessment: An International Journal 2017, 23, 1819–1829, doi:10.1080/10807039.2017.1356683.

22.        Dietert, R.R. Microbiome First Approaches to Rescue Public Health and Reduce Human Suffering. Biomedicines 2021, 9, 1581, doi:10.3390/biomedicines9111581.

23.        Brown, J.H. A Critical Discussion of Some Methods and Standards for Certified Milk. Am J Public Health Nations Health 1938, 28, 1053–1058, doi:10.2105/AJPH.28.9.1053.

24.        Foord, J.A. The Production of Certified Milk. The New England Journal of Medicine 1913, doi:10.1056/NEJM191304241681704.

25.        Alexander, A. Udder Diseases of the Cow and Related Subjects; RG Badger, 1929.

One issue they addressed at length was dose-response (DR) relationships between exposure to a single pathogen cell (but generally a series of higher doses) by ingestion and the likelihood of transmission of disease (illness outcome). Here are some points from the discussion:

• The concept of 'minimum infective dose' is, in Don Schaffner's words, 'BS'. For risk analysis, one requirement is data on DR curves or families of curves (Coleman et al., 2018). Of course, whether those DR curves are from animals, human volunteers, or outbreaks, uncertainties must be addressed for extrapolation to new scenarios of exposure (Coleman, 2025).

• Question: How likely is illness from one Listeria monocytogenes (Lm) cell {for healthy immunocompetent people}?
  The single response from the audience was 1/10^14: 1 chance in 10 raised to the 14th power exposures or servings, 1 illness in 100,000,000,000,000 servings, one illness in 100 trillion servings; negligible risk by many criteria.

  Granted, Lm has caused serious illness and death under certain conditions. 
  CDC reported fatalities for deli meats, pasteurized ice cream/milkshakes, pasteurized soft cheeses (CDC, 2005-2020), and 2 fatalities associated with NY state raw cheese (CDC, 2017).
  No outbreaks or illnesses were confirmed for fluid raw milk (CDC, 2005-2020; Stephenson et al., 2024)

  Lm levels associated with fatalities for hospitalized immunocompromised people in the ice cream outbreak were a million cells or more; no illness was observed in the general population (children, adults, elderly) exposed to approximately a billion Lm cells (Pouillot et al., 2016).

• Question: How likely is illness from one Salmonella cell?
  Responses were 1/100 and 1/10^6 (one in a million), depending on the dataset, serotype, and assumptions (Coleman et al., 2017; Oscar, 2021; Teunis et al., 2022). For one human clinical isolate administered to human volunteers, more than a billion Salmonella cells did not cause illness (Coleman and Marks, 1998; Coleman and Marks, 2017).

• Don Shaffner asked how many Lm are acceptable in foods that do not support Lm growth north of the NY state border, in Canada?
  The response was 100 Lm per mL or gram food, whereas US imposes zero tolerance for any detectable Lm, despite very low infectivity.
  
  Note that few people acknowledge that raw fluid milk is a food that suppresses Lm growth within the typical shelf life period, likely due to competition with the dense and diverse natural milk microbiota (Coleman et al., 2023). Yet the US recalls ready-to-eat foods when Lm is detected, without enumeration, even though 100 Lm/mL in foods not supporting growth is extremely unlikely to cause illness in either the general or more susceptible immunocompromised populations, as noted above.

Risky or Not? People make these decisions every day, sometimes using scientific evidence. Sometimes culture, ideology, politics, and economics influence decisions.

For NY state, only four illnesses were associated with raw milk over the past 10 years. For those who missed previous postings of this figure below, blue bars represent numbers of licenses NY State issued for raw milk dairies from 2005-2022 on the left axis. The orange symbols represent 0, 1, 2, or 3 outbreaks per year in this same time period on the right axis. Despite increasing access, rates of illnesses have not increaed. Neither are trends increasing in any other US state (Stephenson et al., 2024).

Do you have evidence to add to this conversation? Please provide descriptions of the evidence and links in the comment section.

In the previous 10 years, only 4 illnesses from one outbreak were attributed to raw milk in NY state. For 2005-2022, a total of 58 illnesses (4 hospitalizations, no deaths) were attributed to NY State raw milk. CDC reports that all 58 illnesses were associated with campylobacteriosis.

No outbreaks were reported for 4 other pathogens that NY State includes in periodic testing: Listeria monocytogenes; pathogenic E. coli (STEC/EHEC/VTEC/O157:H7); Salmonella; and Staphylococcus aureus (Stephenson et al., 2024).

Although numbers of NY State licences have increased in recent years, no increasing trend in the burden of illness was observed for raw milk. Neither is the rate of illnesses associated with raw milk in any state increasing (Coleman and North, 2023; Stephenson et al., 2024). The figure below lists CDC NORS outbreaks from 2005-2022 associated with raw milk in NY state in orange symbols for the right axis (0, 1, 2, or 3 outbreaks per year) and numbers of NY State licenses for the left axis (10 to 82 licenses per year). The rate of illness adjusted for US Census data for NY State was less than 1 illness in 6 million person-years (Stephenson et al., 2024). Between 2 and 20 people became ill in each NY State outbreak associated with raw milk since 2005.

Although data on raw milk production in NY state is not compiled, evidence exists that demand for raw milk is increasing, despite warnings consistent with the ‘risk perception’ that ‘raw milk is inherently dangerous’. Note that the figure below on California retail raw milk sales is Supplemental FIgure 1 in the first Risk Analysis manuscript on influenza H5N1 (Coleman, 2025).

Risk Analysts defined ‘risk perception’ as follows: ‘a person’s subjective judgement or appraisal of risk’ (Society for Risk Analysis Glossary, 2018); and ‘a blending of science and judgement with important psychological, social, cultural, and political factors’ (Slovic, 1999). Thus, ‘risk perceptions’ are social constructs reflecting ideology, beliefs, and economic interests; ‘risk perceptions’ are not estimations based on the accepted framework for evaluating and incorporating scientific evidence (Marks et al., 1998; Codex Alimentarius Commission, 1999) and quality analysis (Jones and Adida, 2011; Waller et al., 2024; Lathrop et al., 2024) for robust risk analysis. Neither was the work of Chen et al. (2025) based on the established framework for assessing transmission of influenza (Kingley and Nguyen-Van-Tam, 2013; Coleman, 2025).

In contrast to the excellent record of saftey for raw milk in NY state and in the US in recent decades, leafy greens and other raw foods pose high burdens of illness and more severe illness, yet are not prohibited from interstate commerce. In fact, no food, including pasteurized milk, is risk-free.

For the period 1971-2023, raw milk illnesses accounted for 0.5% (104/20,278) of foodborne illnesses in NY state, and 0.098% of illnesses from all transmission sources (animal contact, food, person-to-person, water) in NY state.

Note that the burdens of illness from epidemiologic reports on pathogen-food pairs are inputs to the consensus framework for microbial risk assessment as only the first step, Hazard Identification (Marks et al., 1998; Codex Alimentarius Commission, 1999). Further evidence is required (Exposure Assessment, Dose-Response Assessment, Risk Characterization) to estimate risk, of course with attendant uncertainty.

In contrast to the pending case in FL, no stillbirth or miscarriage has been associated with raw milk in recent decades (Sebastianski et al., 2022; Stephenson et al., 2024). However, pasteurized dairy was associated with 12 cases of premature delivery and 8 miscarriages/stillbirths/fetal deaths (Sebastianski et al., 2022), all associated wtih L. monocytogenes.

Please add references to additional evidence, as well as your questions and comments.

When dogma is founded on belief or myth rather than objective, rigorous scientific inquiry including hypothesis testing, difficulties arise from ‘blind spots’ of individuals and organizations, even professional organizations. In his book Blind Spots: When Medicine Gets It Wrong and What It Means for Our Health (Makary 2024), Dr. Marty Makary quotes Harvard economist Henry Rosovsky: “Never underestimate the difficulty of changing false beliefs by facts.”

From March 2024 up to the present, communications in the media and journal papers have largely reflected ‘dread reckoning’ or overestimations in risk, introduced in the 2012 article entitled ‘Dread Reckoning: H5N1 Bird Flu May Be Less Deadly to Humans Than Previously Thought--or Not’ (Branswell, 2012). Explanations of the relevance of this language and the rigor of the Risk Analysis Quality Test of the Society for Risk Analysis are provided in the appended text box after the ‘Learn More: References’ button at the bottom of this post. ‘Dread Reckoning’ for H5N1 is continuing in 2025, failing to address existing risk analysis quality components developed by risk practitioners.

Miscommunications about avian influenza H5N1 begin with common use of the term HPAI, Highly Pathogenic Avian Influenza. I refer to the virus as ‘avian influenza H5N1’ or simply ‘H5N1’. Exposure to high loads of H5N1 can cause severe and fatal pneumonia and is highly pathogenic in some birds and unprotected poultry workers; H5N1 is mildly pathogenic in dairy cows and dairy workers (Graziosi et al. 2024).

Just as Dr. Makary pointed out the glaring ‘blind spot’ in medicine that there was no ‘downside’ to antibiotics (other than ‘carpet-bombing the microbiota’), pasteurization has evoked a serious ‘blind spot’ common among many journalists, scientists, and industry and professional organizations that there is no ‘downside’ to pasteurizing donor breastmilk and bovine milk, ignoring ‘carpet-bombing’ of the milk microbiota and documented ‘downsides’ that adversely affect human health.

Pasteurization is perceived as a silver bullet, killing pathogens and causing no adverse effects. So many decades have passed mired in the ‘pasteurization blind spot’ that pro-pasteurization bias is deeply entrenched. That systematic bias requires that those with a ‘stake’ in decision making about pasteurizing milks (stakeholders) cultivate healthy skepticism, particularly willingness to fact-check claims with the actual studies and insist upon evidence-based policies and regulations.

When studies are cited in foodborne risk communications, take care to spot half-truths, invalid conclusions not supported by the evidence provided, and distortions of scientific evidence that misinform and intentionally deceive the unwary. For example, see Figure 1 of the Koski study and decide for yourself if the burden of raw milk illness is increasing or if the authors’ interpretation of the outbreak data might reflect pro-pasteurization bias.

Also notice what is left out of communications about milkborne risk. Often what is left out is a relevant reference to valid scientific evidence, particularly references to rigorous peer-reviewed studies. None of the media reports in the past year have acknowledged this fact: neither raw nor pasteurized milks are ‘risk-free’.

Communications of pro-pasteurization advocates commonly leave out evidence, limitations and uncertainties, and assumptions, all inconvenient truths, in order to perpetuate pro-pasteurization myths and maintain status quo to preserve the dominance of pro-pasteurization ‘blind spots’ a bit longer.

The claims made in the media and scientific journals are often not supported by the current body of scientific evidence on benefits and risks of raw and pasteurized milks (Coleman et al. 2021; Dietert et al. 2022). Be on alert for exclusion or dismissal of evidence that does not fit a certain cultural or political belief system or worldview (confirmation bias). Beware of entrenched beliefs masquerading as scientific facts that in reality are not supported by scientific evidence.

Below are some relevant facts that are often left out of public communications about milk benefits and risks, each with a reference that you are encouraged to review and fact-check.

1.      Neither pasteurized nor raw milk is ‘risk-free’.

a.      See Table below for summary of the burden of illness from CDC outbreak data for 2005-2020 and the peer-reviewed manuscript on this dataset (Stephenson, Coleman, and Azzolina 2024).

b. FDA/FSIS assessed pasteurized milk as high risk of severe listeriosis per annum and unpasteurized milk as high risk per serving (FDA/FSIS, 2003); however no listeriosis outbreaks associated with raw milk were confirmed in the CDC dataset for 2005-2020 (Stephenson et al., 2024) .

c.      More deaths are reported from leafy greens (23), pasteurized milk (4), and oysters (2) than the one confirmed death of an adult with severe underlying illness associated with consumption with raw milk (Davis et al. 2016). Note that another death in an adult with severe underlying illness reported in this time period could not be attributed to raw milk consumption.

d.       Higher burdens of illness are reported from leafy greens (16,434 illnesses), oysters (2,408), pasteurized milk (2,111), and many other foods than for raw milk (1,696).

2.      Pasteurized milk is a highly processed food that is linked to adverse health effects.

a.       Significantly higher outbreaks, hospitalizations, and deaths were associated with listeriosis in pasteurized dairy from 2007-2020 of listeriosis compared to raw dairy (Sebastianski et al. 2022).

b.       Stillbirths, miscarriage, premature delivery were reported for pasteurized dairy, not raw dairy (Sebastianski et al. 2022).

c.        Heating milk (boiling and pasteurization) denatures milk proteins, increasing allergenicity and contributing to inflammatory disease (Abbring et al. 2019; 2020).

d.       Allergy to and intolerance of pasteurized milk is estimated to have a substantial public health burden in the US, with 30-37% intolerance of thermally treated milk from recent US surveys (Warren et al. 2022; Warren et al. 2024). Approximately 15 million US consumers (4.7% or nearly 1 in 20) are affected by thermally-treated/pasteurized milk.

e.       Industrial processing of milk (heating, filtration, pressure, drying, freezing) causes denaturing, aggregation, and loss of function of cow milk antigens (α-lactalbumin, β-lactoglobulin, serum albumin, caseins, bovine serum albumins, and others), reductions in concentrations of bioactives (immunoglobulins, cytokines, peptides, lipophilic components, and microbiota), and impairs immunologic tolerance mechanisms (Jensen et al., 2022).

3.      Approximately 15 million raw milk consumers benefit from access.

a.       A recent government survey estimated 4.4% of US population consumes raw milk (Lando et al., 2022).

b.       Multiple sources report consumption of raw milk is increasing, not decreasing (NielsenIQ figures cited by (Aleccia 2024; Lyubomirova 2024); Figure below included in Coleman manuscript under review in Risk Analysis).

c.       CDC reported 1,696 raw milk illnesses for 2005-2020; Stephenson et al., 2024) but not inflammatory disease (Dietert et al. 2022).

d.       Raw milk was tolerated by children with allergy to pasteurized milk, and pasteurized milk induced adverse effects (Abbring et al. 2019).

e.        Raw milk has a dense and diverse microbiota, similar to the breastmilk microbiota, both inducing benefits to gut microbiota, immune system function, and suppressing growth of pathogens (Coleman et al. 2021; Dietert et al. 2022; Coleman et al. 2023; Coleman, submitted).

f.        Raw milk was associated with increased functional richness of the gut microbiota (notably genus Lactobacillus and Lactococcus and the short chain fatty acid valerate) and participants with higher than median anxiety scores showed significant score reduction for stress and anxiety (Butler et al., 2020).

4.      Illness associated with raw milk is not increasing in the US or any US state based on recent CDC data.

a.       No significant increase was reported for illnesses associated with raw milk outbreaks from 1998-2018 or numbers of outbreaks from 2005-2018 (Koski et al. 2022, Figure 1 ) or 2005-2020 (Stephenson et al., 2024, Figures 12 and 13 below).

5.      Regarding children, consuming raw milk complete with intact natural microbes (microbiota) is beneficial to health.

a.       Just as children benefit from raw breastmilk and its protective microbiota, children (and adults) also benefit from raw cow milk complete with its protective microbiota that enhance health of gut, immune, nervous, and respiratory systems (Coleman et al., 2021; Dietert et al., 2022).

b.       No child has died in the US from consuming raw milk in recent decades based on CDC data for 2005-2020 (Stephenson et al., 2024).

c.        Children with allergies to pasteurized milk tolerate raw milk consumption with no adverse effects (Abbring, 2019).

d.       Children consuming raw milk in multiple large studies developed no diarrheal illness, significantly fewer respiratory and ear infections, protection from inflammatory disease including atopy, asthma, and eczema, and improved immunologic and lung function later in life (Perkin and Stranchan, 2006; Depner et al., 2013; Loss et al. 2015; von Mutius 2016; Wyss et al., 2018; Brick et al., 2020; Dietert et al. 2022).

6.      Claims that raw milk is ‘inherently dangerous’ and that ‘risks exceed benefits’ are unfounded and not supported by the body of scientific evidence. 

a.    Recent trends in unpasteurized fluid milk outbreaks, legalization, and consumption in the United States (Whitehead and Lake, 2018): 
The study is based on CDC data from 2005-2016 documenting 1,903 illnesses associated with pasteurized milk and 1,735 illnesses associated with raw milk. The rate of raw milk related outbreaks is decreasing, meanwhile the consumption of raw milk is increasing. The authors concluded that, “Controlling for growth in population and consumption, the outbreak rate has effectively decreased by 74% since 2005.” The study suggested that the improving food safety record is the result of expanded safety training for raw milk dairy producers.  

b.      Examining Evidence of Benefits and Risks for Pasteurizing Donor Breastmilk (Coleman et al., 2021). This application of evidence mapping, a formal benefit-risk methodology with demonstrated utility as a bridge between opposing world views, structured evidence regarding the controversial issues underpinning human donor milk bank policies requiring pasteurization of donor breastmilk. Seventy-one studies were cited documenting evidence for benefits and risks of raw breastmilk for infants. Evidence of benefits was clear, convincing, and conclusive, while evidence for infectious disease risks to infants consuming raw breastmilk was limited. Supporting studies provided evidence of plausible mechanisms of benefits of ‘seeding and feeding’ the infant gut ecosystem, notably providing ‘colonization resistance’ or protection against pathogens and stimulating balanced development of infant immune systems. The study recommends broad societal deliberations of the body of evidence to resolve misunderstandings and mixed messages that invoke fear and dread so that evidence-based policies might maximize benefits and minimize risks to NICU infants.

c.        Nourishing the Human Holobiont to Reduce the Risk of Non-Communicable Diseases: A Cow’s Milk Evidence Map Example (Dietert et al., 2022). (Dietert et al., 2022). 
This study builds on the previous applications of evidence mapping as a bridge, structuring evidence that might support wider deliberation between those with opposing world views about benefits and risks of raw and pasteurized donor milks from cows. The study cited 135 studies illuminating raw bovine milk as a superfood complete with its natural microbiota intact and chosen by humans for 200 million years. A significant focus of the study is the impact of raw bovine milk on the immune system, specifically on the microimmunosome that significantly determines risk of the primary global health threat, non-communicable and inflammatory diseases (NCDs; allergy, asthma, eczyma, obesity). As noted for the breastmilk evidence map, consistent evidence of raw bovine milk benefits (promotion of gut, immune, and lung health; protection from infectious diseases and NCDs) and limited evidence of risks of infectious disease were documented in large human studies, many focusing on children.
Notably, prior discussions of the evidence focused primarily on raw milk outbreaks. This study included NCDs and significant findings from microbial risk assessments: i) Listeria monocytogenes was not considered a main hazard in raw milk and could be mitigated by cold chain and other factors; and ii) risk associated with Shiga toxigenic E. coli had subsided to negligible levels in Italy, and that models for campylobacteriosis, listeriosis, and salmonellosis overestimated risk. The study recommends that the evidence map for raw bovine milk similarly support broad societal deliberations of the evidence to begin a paradigm shift away from 20th century ideas about microbes as germs that will kill us and towards the advancing understanding of our microbiota as our partners in health and raw milk as a superfood ‘seeding and feeding’ human and microbial cells in the gut. Indeed, “restoring health may be tied to restoring diverse microbes to the industrial diet dominated by [highly] processed foods, including pasteurized milks”.

d.       Trends in Burdens of Disease by Transmission Source (USA, 2005–2020) and Hazard Identification for Foods: Focus on Milkborne Disease (Stephenson et al., 2024).
The study assessed trends for CDC data from all transmission sources for 2005-2020 and conducted the first element of microbial risk assessment, Hazard Identification, for food-pathogen pairs. The burden of illness and mortality was dominated by person-to-person transmission. Foodborne disease accounted for 21% of the disease burden with no increasing trend. Foods representing the greatest hazards were identified for campylobacteriosis (pasteurized and raw milk), illness from Shiga toxigenic E. coli (leafy green vegetables and beef), listeriosis (melons and pasteurized solid dairy products), and salmonellosis (poultry and leafy vegetables). Fatal foodborne disease was dominated by fruits, vegetables, peanut butter, and pasteurized dairy. No increasing trend of raw milk illnesses were observed overall for any state, nor did rates of illness increase after legislation to allow greater access to raw milk. The authors question the common claim that raw milk is an “inherently dangerous food”. The available epidemiologic and microbiologic evidence conflicts with assumptions of zero risk for pasteurized milk and increasing trends in the burden of illness for raw milk.

7.      Scientific evidence fails to support the hypothesis that avian influenza H5N1 transmits to humans by ingestion.

a.       Avian influenza H5N1 is not a foodborne pathogen that causes stomach flu in humans, but it can cause respiratory infection, pneumonia, and pink eye (inflammation, conjunctivitis) (Jones and Adida 2011; Lockhart, Mucida, and Parsa 2022; AbuBakar et al. 2023; Graziosi et al. 2024).

b.       The reservoir for avian influenza H5N1 is birds, NOT dairy cattle.

c.        All lines of evidence for assessing influenza transmission (Killingley and Nguyen-Van-Tam 2013) fail to support the hypothesis about oral transmission of avian influenza in humans as documented below.

i.       Avian influenza H5N1 is not highly pathogenic or highly virulent for dairy cows or dairy workers (Graziosi et al. 2024).

ii.       Mild eye inflammation was reported for 41 dairy workers in five states (36 in CA, 2 in MI, 1 each in CO, NV, and TX) exposed to infected cows (CDC 2025), despite limited transmission to dairy herds in 16 states and higher transmission to herds in California.

iii.       No influenza disease transmission was observed for non-human primates inoculated with a high oral dose of H5N1; in contrast, nasal inoculation at the same dose caused mild illness and inoculation into the deep lung caused severe and fatal illness in non-human primates (Rosenke et al. 2024). The most reliable animal model for extrapolation to humans, the non-human primate, has effective innate barriers to oral transmission of avian influenza H5N1.

iv.       None of the ferret, mice, and cat studies among the available 44 inoculation studies for H5N1 are suitable for extrapolation to oral exposures to the human gastrointestinal tract (Coleman, under review in the journal Risk Analysis).

v.       No epidemiologic evidence documents oral transmission of H5N1 to raw milk consumers. No oral infections or pneumonia were documented in dairy workers or consumers.

vi.       More than 263,000 gallons of H5N1-positive raw milk (~4.6 million servings) circulated in the CA retail market last November (Coleman, manuscript under review), with no human influenza cases reported (CDC, 2025).

vii.       Weak pathogenicity and low virulence of bovine H5N1 strains are consistent with evidence that the virus strains adhere weakly to human receptors (Santos et al. 2025).

viii.       Validated models of transmission for respiratory and ocular exposure exist for influenza A (Jones and Adida, 2011), but no mechanistic models exist for oral transmission of H5N1.

b.      Transmission of H5N1 virus between dairy herds in 2024 is consistent with the common practice of movement of animals to farms other than those where they were born (Nguyen et al. 2025), practices uncommon in smaller dairies licensed to sell raw milk direct to consumers.

c.       Mandatory testing before animal movement contributed to reduced transmission to other dairy herds in US states (Nguyen et al., 2025).

d.      No evidence exists for the hypothesis that milk is a vehicle for H5N1 disease transmission between animals, between herds, or to human consumers.

8.      Evidence of the presence of viral or bacterial pathogens in milk or on surfaces is insufficient to estimate risk of illness in raw milk consumers with attendant uncertainties, consistent with risk analysis principles and established guidance on risk analysis quality (RAQT of the SRA, 2020).

a.       Presence of a pathogen is an invalid predictor of risk of human illness.International consensus defines four required elements for assessing microbial risk: Hazard Identification; Exposure Assessment; Dose-Response Assessment; and Risk Characterization (Codex Alimentarius Commission, 1999).

b.       Estimating risk requires cohesive knowledge well characterized body of knowledge by which to reliably scale doses and responses in animals to humans (Swearengen, 2005; Swearengen, 2018; Zheng, Song, and Zheng 2024).of: i) mechanisms of infection in humans; ii) ecological and mathematical relationships between microbial load (ingested or inhaled or contacted on surfaces) and transmission of human illness by route (oral, inhalation, contact); and iii) doses causing no illness, mild illness, and severe illness by route (McClellan et al. 2018; Coleman et al. 2018).

c.       Extrapolation from animal models requires a well-characterized body of knowledge by which to reliably scale doses and responses in animals to humans (Swearengen, 2005; Swearengen, 2018; Zheng, Song, and Zheng 2024).

i.       Ferrets, mice, and cats are not equivalent to humans, and host extrapolation would require data on anatomical, physiological, immunological, and behavioral differences between humans and laboratory animals

ii.       Nor are non-human primates equivalent to humans.

iii.       If extrapolation is necessary, non-human primates are more representative of human systems than other laboratory animals based on a long history of risk analysis.

iv.       Animal models that can accurately replicate both fatal and non-fatal human infections, as well as consistent time courses and severities, are relevant for extrapolation to human disease transmission.

d.        Quality risk analysis studies commonly document no disease transmission at low pathogen exposures (ingested or inhaled doses or delivered pathogen load) and increasing likelihood and severity of illness at increasingly higher loads, influenced by our microbial partners in health, our microbiota (Coleman et al., 2008; McClellan et al. 2018; M. Coleman et al. 2018; Lathrop et al., 2024; Waller et al., 2024).

Here is my perspective of the case for and against worrying about avian influenza H5N1 and cats, followed by highlights from key references.

Highlights of Evidence from Published Studies

Multi-dose inoculation study by Vahlenkamp and colleagues at Federal Research Institute for Animal Health in Germany and Intervet UK (2008)

o   No disease transmission was observed for cats inoculated (combined oculo-nasopharyngeal route) at the lowest three doses (1, 100, and 10,000 egg infectious dose units (EID50), relative viral counts documented to infect 50% of embryonated chicken eggs).

o   Two of three cats inoculated at the highest dose (a million times the EID50) developed clinical symptoms and fatal outcomes. The third cat inoculated at the highest dose recovered and developed protective antibodies.

o   Cats immunized with low pathogenic H5N6 were fully protected from subsequent challenge at the highest H5N1 dose (a million times the EID50).

Review by Sreenivasan and colleagues from University of Kentucky (2024)

o   Cats exposed to H5N1 can show no signs of clinical infection or signs including conjunctivitis, periocular swelling, depression, lethargy, and oculonasal discharge, as well as severe and fatal signs of respiratory distress and neurological signs (e.g., circling, blindness).

o   Fatal infections were reported in small numbers of cats as sporadic cases or outbreaks in Germany, Poland, South Korea, and the US.

o   A poultry farm outbreak in Italy was not associated with disease transmission to a domestic cat and 5 dogs on the farm.

Systematic review by Coleman and Bemis of University of Maryland  (2024)

o   Of 41 studies on natural infections of avian influenza viruses in felines from 2003 through April of 2024, 27 studies reported on domestic cats in 13 countries (Austria, China, Egypt, France, Germany, Indonesia, Iraq, Italy, Poland, Spain, South Korea, Thailand, US).

o   Of avian influenza subtypes, H5N1 was most frequently reported in cats, followed by H5N6, H7N2, H9N2, and H3N8.

o   Although the authors offered some estimates for mortality rate, few studies reporting fatalities documented the actual number of cats exposed, and serology studies are inconsistent with high fatality rates.

o   Indonesia reported ~100 of 500 domestic cats sampled in 2008 were seropositive for H5N1 antibodies.

o   Some workers in direct contact with low pathogenic avian influenza H7N2-infected cats in shelter outbreaks became seropositive.

o   The authors report that transmission route (direct contact, ocular, oral, respiratory) and delivered viral doses likely impact disease presentation and severity in cats, consistent with general principles of dose-response assessment for humans and other animals.

Seroprevalence study by Cavicchio and colleagues from the Experimental Zooprophylactic Institute of Venice (IZSVe), Italy  (2024)

o   Influenza A viral infections in cats are sporadic and self-limiting even when high morbidity and mortality is reported in areas where outbreaks are reported in wild and domestic avian species.

o   Samples from healthy feral cats living in outdoor feline colonies hosted by companion animal shelters in 7 provinces in northeastern Italy (2021-2022) were negative for influenza A (and H5N1) in all 385 oropharyngeal swabs. Only one of 279 serum samples was H5-positive.

o   Considering recurring outbreaks for domestic (263) and wild birds (24) reported in the area in the same time period of the study, authors conclude transmission of influenza A including H5N1 to cats is rare.

Seroprevalence study by Duijvestijn and colleagues at University of Utrecht, The Netherlands and Stray Cat Foundation Netherlands (2024)

o   Serum was confirmed positive for antibodies to avian influenza H5 in 83 of 701 clinically healthy rural stray cats (65 confirmed) from nature preserves and nearby dairy farms and in none of 871 urban domestic cats sampled from 2020 to 2023 in The Netherlands.

o   Pharyngeal swabs or lung tissues were negative for influenza A virus in 230 cats with acute respiratory or neurologic signs.

o   Higher seroprevelance in stray cats was considered by the authors as evidence for more frequent exposure due to foraging (hunting and eating) wild birds.

o   The study authors recommend that people handling cats with respiratory or neurological signs use appropriate personal protective equipment (e.g., gloves, face shield, mask).

Some additional studies that may be of interest are listed below. If you would like a follow-up blog on additional studies, please submit a comment with your interest.

• Highly Pathogenic Avian Influenza (HPAI) H5 Clade 2.3.4.4b Virus Infection in Birds and Mammals (Graziosi et al., 2024)

• Burden of Common Respiratory Pathogens Among Cats in China (Umar et al., 2025)

• Serological Exposure to Influenza A in Cats from an Area with Wild Birds Positive for Avian Influenza (Villanueva-Saz et al., 2024)

• The Evolution and Epidemiology of H3N2 Canine Influenza Virus After 20 Years in Dogs (Wasik et al., 2024)

This blog will address what we know from this ‘correspondence’ in reference to full studies published in the peer-reviewed literature. It will also introduce questions about extrapolating data on transmission and infection in animal models to humans, as well as what is uncertain or unknown or assumed. 

Let’s examine the lines of evidence from the brief ‘correspondence’.

1.      Researchers anesthetized five laboratory mice (Balb/cJ) and inoculated one dose-level (50 μl containing 3 million pfu) of a sample of raw milk from New Mexico cows (NM#93) infected with influenza A H5N1 (H5N1 hereafter), also termed highly pathogenic avian influenza. The raw milk sample was inoculated in the back of the throats of the five anesthetized mice with a micropipette. Researchers reported that these five mice were noted to have swallowed, but also to have had milk in their nasal cavities. The only signs of illness noted were ruffled fur and lethargy.

2.      Take a look at evidence of viral detection reported for these 5 mice, euthanized at day 4 after inoculation (Figure S3 below). No evidence of viral detection was reported in intestine or feces as would have been expected if H5N1 caused intestinal flu. The highest titers were reported in lung, trachea, and nasal turbinates (the networks of bones, vessels, and tissue within nasal passageways, markedly different in mice and humans). This pattern is consistent with transmission via the respiratory system.

3.      The authors’ Table 1 reported results on heat inactivation for 4 milk samples positive for virus (NM#93, NM#115, KS#3, and KS#6) and controls not subject to heat. A further claim is that over five weeks, antiviral activity of refrigerated raw milk samples was demonstrated, but the report of a 2-log viral titer decrease by five weeks was not accompanied by raw data or data on rates of inactivation over the 5-week refrigeration period.

4.      Now take a look the authors’ Table S1 below. The authors report that the cow milk samples obtained from an affected herd in New Mexico were tested by quantitative RT-PCR (qPCR) for two viral RNAs, the influenza virus matrix (M) and hemagglutinin (HA). Note that determining infectivity of PCR-positive raw milk samples requires additional testing, typically in animal models or tissue culture cells. Milk samples were inoculated into embryonated chicken eggs and Madin-Darby canine kidney (MDCK) cells to test for infectivity. Note that this table does not address whether virus amplification was confirmed in one or both of these assays. Three of 11 samples provided estimates of viral titer above the limit of detection, and three samples failed tests for infectivity. Eight samples reportedly amplified intact infective virus.

5.      The authors also reported detection of virus in mammary glands of 2 of 5 mice and conclude raw milk positive for H5N1 poses a risk when consumed untreated.

Now, let’s examine other lines of evidence that influence interpretation of the results of the ‘correspondence’.

Regarding points 1 and 2 above, a 2023 study (Effects of Extended-Release Buprenorphine on Mouse Models of Influenza) states the following caution:

‘Analgesia is rarely used’ in mouse models of influenza because of ‘concerns that [such] treatment might have confounding effects on primary study parameters such as the course of infection and/or the serological response to infection.’

We do not know if anesthesia or problems with inoculating technique or just that mice are obligate nose-breathers might have contributed to spreading inoculum into the nasal cavities of the five mice. What is apparent is that respiratory infection, not GI infection, developed.  

This ‘correspondence’ does NOT demonstrate oral infectivity of H5N1 in the five mice.

Similarly, a recent review entitled Animal Models for Influenza Research: Strengths and Weaknesses noted limited utility for mouse models in the study of influenza A virus transmission, due to differences between mouse and human immune systems, and differences in toll-like receptors, defensins, and antibody classes (IgGs). Also, replication of Influenza A viruses occurs in the lower respiratory tract in mice, unlike replication predominantly in the upper respiratory tract of humans and ferrets. These researchers note that experiments with small groups of animals (5 is a small group) are subject to misinterpretation of results that may not sufficiently characterize transmission and pathogenicity in the animal model. The 5-mouse ‘correspondence’ seems grossly insufficient to permit any extrapolations to humans, in my view, without definitive data on multiple exposure pathways.

Regarding points 3 and 4, antiviral activity was demonstrated for raw milk, though raw data and the timeline for the 2-log reduction in viral titer in raw milk samples was not provided. It is possible that for the 8 of 11 samples below the detection limit in Table S1, natural antiviral activity could eliminate infectivity in the egg and canine tissue culture assays. We do not know if any of the remaining 10 raw milk samples in Table S1 with titers of 0.2 million pfu/mL (#119), 500 pfu/mL (#90), or the 8 samples below the limit of detection would cause respiratory infections in mice that were observed with inoculation of the sample with the highest titer (60 million pfu/mL, #93) in the 5 mice for this ‘correspondence’.

Point 5 raises more questions than it answers.

The observation of viral RNA in mammary glands of 2 out of 5 inoculated mice is puzzling. Were mammary tissues assayed by PCR and not for infectivity? If so, the ‘correspondence’ does not document presence of infective virus in mouse mammary tissue.  

The conclusion that raw milk positive for H5N1 poses a risk when inhaled by mice has no bearing on making scientific inferences for extrapolation to as yet only ‘theoretical’ risk to humans who consume or inhale raw milk from affected cows.

At present, the only transmission pathways demonstrated for the current H5N1 in humans are respiratory (e.g., 455 total deaths among 862 human cases in China, Egypt, Indonesia, and Vietnam from 2003-2009) and ocular (2 mild cases of conjunctivitis in US dairy workers in 2024). Remember that influenza A is NOT among the 7 classes of viruses that infect the gastrointestinal system and cause intestinal flu (i) adenovirus; ii) astrovirus; iii) enterovirus; iv) hepatovirus; v) norovirus; vi) rotavirus; and viii) sapovirus).

Feel free to comment or to raise more questions about the ‘correspondence’ and about how data from animal models can be reliably extrapolated to assess risks for humans.

I begin this blog as the last, with Helen Branswell’s 2012 article in Scientific American entitled ‘Dread Reckoning: H5N1 Bird Flu May Be Less Deadly to Humans Than Previously Thought--or Not’.

The author conveyed the limitations of data available in 2012 that might lead to overestimated risk. Pooling the data from across the globe as though exposures, populations, and medical preparedness in every country were equal is dangerous business.

Risk analysts and many scientists are trained to question the representativeness of observational or experimental data for extrapolation to other populations and conditions. Let’s start by exploring the fallacy of assuming that these pooled mortality rates from across the world are representative of all individuals and populations at all future times.

Take another look at this paragraph from my previous blog and build on that evidence to assist our deliberations together.

The World Health Organization compiled evidence of 888 human cases, 463 fatal, for years 2003-2024. Since 1997, 909 human cases from 23 countries were associated with H5N1 (predominantly 2.3.4.4b clade). Thirteen of 28 human cases reported since 2021 are associated with clade 2.3.4.4b. This virus was documented in migratory birds in Africa, Asia and Europe in 2020, and spread to North America in 2021. Some asymptomatic cases were noted, and human symptoms range from no or mild illness to severe pneumonia with respiratory failure, encephalitis, and multi-organ failure.

If you click on the red text above, you’ll see a WHO table or a link to download WHO data listing portions of the data on 909 cases reported in 23 countries. Here is one more WHO table that is helpful in today’s deliberations about assuming the pooled 50% mortality rate applies to you and me, today and into the future.

Now let’s consider what we know and what we don’t know about mortality across countries and across time, from 1997 to present.

For illustration purposes, I selected two groups of countries and the period 2003-2021 to begin our deliberations on today. In parentheses for each country, you’ll see the percentages of 862 total influenza A H5N1 cases in this period and the percentages of the 455 total deaths.

1. China (6%; 7%); Egypt (42%; 26%); Indonesia (23%; 37%); and Vietnam (15%; 14%)

2. Chile, Ecuador, Spain, the UK, and the US (no reported cases or deaths in this period)

For the first group of four countries with cases and deaths in this period, here are estimated case-mortality percentages within each country for each year from 2003-2021. Note that the 100% values represent 3-5 fatal cases for given years for China and Vietnam.

Now, let’s look at the most recent 5 years of data for these four countries described by CDC here.

Next, let’s look at the data for cases in three recent years from the second group of 5 countries that had no reported cases in prior years.

So, given trends in numbers of cases and fatalities, plus percentages and other outcomes (asymptomatic and mild cases), over 2003-2021 and 2022-2024, here are some questions that I would pose.

1.       Why do you think Table 1 values from 2003-2009 are so different from those in Tables 2 and 3 from 2022-2024?

2.       Why do you think influenza A H5N1 caused asymptomatic and mild cases in Table 3 compared to single critical and fatal cases? Compared to fatalities from 2003-2009 in Table 1?

3.       Does it look to you like the overall 50% mortality rate from 2003-2009 in Table 1 can be extrapolated directly to the future for any country and any individual, without additional information explaining the trends illustrated here?

4.       What more do we need to know to assess the risk of infection, severe illness, and mortality for consuming raw milk that is PCR-positive for viral particles or viral fragments of influenza A H5N1?

If you read my first two blogs on influenza A H5N1, you may expect that mechanistic evidence of oral transmission to humans is tops on my list of unknowns for question 4.

The study by Gambotto and colleagues discusses viral transmission, clinical features, and host restriction and pathogenesis. Influenza A transmission to humans is well documented only via the respiratory system (inhaling droplets or dust particles contaminated by the virus) or direct contact with contaminated objects, then touching the eyes, nose, or mouth. These are the only two ‘theoretical’ transmission routes that CDC researchers are now exploring with experimental models (ferrets) as described in the May 10th update on H5N1. Katella provides additional perspective on influenza A in her post on Yale Medicine.

Remember, there is no evidence that influenza A passes through stomach acids, digestive enzymes, and human innate immune defenses that inactivate enveloped viruses by the oral route. The following viruses are documented in a recent review to be transmitted to humans by oral ingestion:

1.    adenovirus

2.    astrovirus

3.    enteroviruses

4.    hepatoviruses

5.    norovirus

6.    rotavirus

7.    sapovirus

Influenza A and other influenza viruses are NOT documented to transmit to humans by ingestion. FDA and USDA had made this determination years ago, but they have been silent about their assessment, perhaps because of their long-standing fears about raw milk.

Second, the high mortality rates in Table 1 are primarily associated with respiratory infections after prolonged direct contact with sick, dying, and dead animals, typically wild birds and domestic poultry. Only in recent times is there awareness that respiratory protections, biosecurity, and safety training can likely prevent occupational and other exposures to influenza A H5N1. I see no evidence that consuming foods containing influenza A H5N1 (nucelic acid fragments or intact viral particles detectable by PCR) has caused illness or death in humans.

Please comment with questions and other evidence on influenza A H5N1 transmission to the respiratory tract, the eye, and the gut.

I found that I agree with much of the content of Helen Branswell’s 2012 article in Scientific American entitled ‘Dread Reckoning: H5N1 Bird Flu May Be Less Deadly to Humans Than Previously Thought--or Not’. Her title and her content are excellent, particularly her language choice in the first lines of her article that are extremely relevant to risk analysts.

• ‘Dread’ because it is a strong motivator, especially for public health officials whose best interests are likely protecting people from unnecessary suffering via infectious agents.

• ‘Reckoning’ because estimations of risk in the public health context rarely seem to address uncertainties or the quality of the body of evidence and of the inferences supporting the estimate.

• ‘Fear’ because a worldview that microbes are pathogens that will kill us is likely not evidence-based.

• ‘Worst-case scenario’ because ‘a simple math problem’ of estimating risk is simple only if uncertainty, quality of the data and inferences, and distinctions between correlative and causal data are ignored.

She cites the limitations of available data that may overestimate risk by focusing on the most severely affected and the fallacy of assuming those rates are representative of generally healthy populations around the world.

Is the ‘worst-case’ predicted from 2012 being realized in 2024? Some evidence to consider is summarized below.

The World Health Organization compiled evidence of 888 human cases, 463 fatal, for years 2003-2024. Since 1997, 909 human cases from 23 countries were associated with H5N1 (predominantly 2.3.4.4b clade). Thirteen of 28 human cases reported since 2021 are associated with clade 2.3.4.4b. This virus was documented in migratory birds in Africa, Asia and Europe in 2020, and spread to North America in 2021. Some asymptomatic cases were noted, and human symptoms range from no or mild illness to severe pneumonia with respiratory failure, encephalitis, and multi-organ failure.

Ironically, no mention was made by CDC, FDA, or USDA about applying the Tool for Influenza Pandemic Risk Assessment (TIPRA), available for free from the WHO website, before generating their risk communication messaging about avoiding raw milk and raw milk products.

The 8-page joint report on the Preliminary Assessment of Recent Influenza A (H5N1) Viruses dated 23 April 2024 by the Food and Agriculture Organization, the World Health Organization, and the World Organization for Animal Health states the following.

1.       ‘Of the 28 human cases of A(H5N1) detections reported since the beginning of 2021, all were sporadic infections in people exposed to A(H5N1) viruses through direct or indirect contact with infected birds, infected mammals or contaminated environments, such as live poultry markets or other premises with infected animals. Among these cases, there has been no reported human-to-human transmission.’

2.       ‘It is recommended that national authorities fully assess the risk among occupationally exposed persons using active case finding and serologic methods, as well as work with national agencies to understand the exposure and risk from milk and milk products.’

3.       ‘Investigations are ongoing to understand the risk to humans from consuming milk contaminated with A(H5N1) virus.

FAO/WHO continues from point 3 to stress the importance of following ‘safe food practices’. Yet the concluding point that FAO and WHO ‘strongly advise the consumption of only pasteurized milk and to avoid consuming raw milk,’ like the CDC, FDA, and USDA position, is not evidence-based. Consider the evidence in the analyses below.

• Scientific Opinion on the Public Health Risks Related to the consumption of Raw Drinking Milk (2015)

• Nourishing the Human Holobiont to Reduce the Risk of Non-Communicable Diseases: A Cow’s Milk Evidence Map Example (2022)

• Trends in Burdens of Disease by Transmission Source (USA, 2005–2020) and Hazard Identification for Foods: Focus on Milkborne Disease (2024)

At this point, there are more gaps in knowledge and unanswered questions than mechanistic understanding of influenza A H5N1 viral transmission. Perhaps the only certainty is that evidence is grossly incomplete to support the presumption that Influenza A transmission to humans is anything but by direct contact with groups of infected animals.  

Now let’s briefly consider the evidence on cats.

CDC’s journal Emerging Infectious Disease includes an Early Release Article entitled ‘Highly Pathogenic Avian Influenza A(H5N1) Clade 2.3.4.4b Virus Infection in Domestic Dairy Cattle and Cats, United States, 2024’. The authors report the following.

1.       ‘Ingestion of feed contaminated with feces from wild birds infected with HPAI virus is presumed to be the most likely initial source of infection in the dairy farms.’

2.       Half of a group of 24 cats fed raw milk from infected cows died with antemortem clinical signs including ‘copious oculonasal discharge’ and postmortem pathologies including ‘multifocal meningeal hemorrhages’ in the cerebrum and pneumonia, with damage to lung, heart and all layers of the retina. This information is consistent with respiratory and ocular infection, not gastrointestinal infection.

3.       Brain has been suggested as the best diagnostic sample to analyze for cats, and neurological signs are well documented in cats.

4.       ‘Most cases in cats result from consuming infected wild birds or contaminated poultry products.’

5.       ‘Exposure to and consumption of dead wild birds’ could not be ruled out for the 12 cats who died or the 12 cats who survived consumption of potentially infective raw milk.

6.       One study was cited that provided experimental evidence of transmission of influenza A H5N1 to cats via artificial inoculation (intratracheal) and by feeding cats virus-infected chickens.

A subsequent study ‘Emergence and Potential Transmission Route of Avian Influenza A (H5N1) Virus in Domestic Cats in Poland, June 2023’ determined that contaminated poultry meat was a potential source of transmission for one of 29 cats in this study. The viral sequences from cats appeared highly related to a stork isolate. Infection of tissue culture cells isolated from canine, feline, and human tissues, of course lacking innate and adaptive immune system components including the healthy gut microbiota, was noted for a viral isolate from this study.

Based on nearly three decades considering microbial risk analysis largely for aerosol and ingestion transmission routes, the available data from cats appears insufficient to make any inferences about foodborne transmission of influenza A H5N1 to humans, from contaminated poultry or potentially contaminated raw milk. It appears that contaminated wild or domestic birds likely transmit influenza A H5N1 to respiratory and ocular systems of cats, not to the gastrointestinal tract.

Some uncertainties to consider in closing for today:

1.       Are the viral particles in raw milk samples infectious?

2.       If so, how long do infected cows shed infective virus in their milk?

3.       What ingested doses cause asymptomatic, mild, and severe disease in cats, controlling for inhalation exposures?

4.       At what ingested doses do the antiviral properties of raw milk protect cats from symptomatic infection?

5.       At what doses do innate and adaptive immune systems of healthy humans protect against infection for ingested influenza A H5N1?

6.       At what doses do healthy gut microbiota protect against infection for ingested influenza A H5N1?

Clearly, there is much to learn about transmission of influenza A H5N1. At present, the risk communication messaging from CDC, FDA, and USDA is not evidence-based and ignores uncertainties about the quality of data and inferences.

Webinar moderators were a Past-President of SRA in decision analysis,
D. Warner North, and a food microbiologist, Isabel Walls. Medical microbiologist Peg Coleman presented on Deliberating Evidence for Milkborne Risk Analysis based largely on three recently published peer-reviewed studies: 

• Trends in Burdens of Disease by Transmission Source (USA, 2005–2020) and Hazard Identification for Foods: Focus on Milkborne Disease

• Lessons Identified from Applications of the Risk Analysis Quality Test Release 1.0

• Suppression of Pathogens in Properly Refrigerated Raw Milk

The learning objectives appended were structured around deliberating evidence for conducting microbial risk assessments for foods. The webinar offered evidence on a series of topics with polls to encourage active audience engagement in deliberating evidence for assessing milkborne risks. 

Topic descrpition

Few risk analysis practitioners might argue that any food is risk-free. Even fewer might know that US government Agencies classified both raw and pasteurized bovine milks, as well as deli meats, as high risk for severe listeriosis in 2003. Scientific advances characterizing raw foods microbiology, particularly benefits and risks of the milk microbiota, motivates further consideration of the Codex Alimentarius Commission international consensus principles for microbial risk assessment, calling for re-assessments over time and re-evaluation as new relevant scientific data become available. Speakers will introduce recent scientific advances that provide new lines of evidence and wider context for assessing risks of raw and ready to eat foods. The webinar series will address critical needs for deliberation of scientific evidence and analysis in light of misinformation or disinformation about risks and benefits. Participants will develop essential skills for deliberating evidence and assumptions, reducing bias and misinformation, and cultivating a culture of quality risk analysis and food safety.

Webinar Abstract

The webinar offered evidence and assumptions on Exposure Assessment, Dose-Response Assessment, Risk Characterization, and Risk Management from a 2003 report on estimation of relative risks of severe listeriosis for 23 ready-to-eat foods including raw and pasteurized fluid milks. Evidence from subsequent studies on these topics plus Hazard Identification were presented. Webinar participants were invited to deliberate the evidence relative to Codex principles: 1) the need for re-assessment in light of subsequent epidemiologic data on foodborne disease (CDC dataset, 2005-2020); and 2) the need for re-evaluation based on advances in scientific knowledge. Questions raised in a recent publication on retrospective application of the SRA Risk Analysis Quality Test (RAQT) to the listeriosis risk assessment were considered.

Learning Objectives:

1.       Expand knowledge and skills for deliberating evidence for conducting microbial risk assessment for raw/ready-to-eat foods including fluid milks.

2.       Gain knowledge of risk analysis quality for raw/ready-to-eat foods.

3.       Increase understanding of potential sources of bias, misinformation, and disinformation about science and risk analysis for raw/ready-to-eat foods.

In March of 2024, dead wild birds on a TX dairy farm and unusual symptoms in older dairy cows (decreased lactation, low appetite, other clinical signs) triggered sampling of affected cows (oropharyngaeal swabs) and their milk. On March 25th, Texas Animal Health Commission confirmed samples were positive for HPAI. A dairy worker on this farm with eye inflammation was also confirmed positive for HPAI, though it is unclear if the worker had contact with both the dead birds and the affected cows.

On April 9th, the World Health Organization (WHO) stated the following about the TX case. “This is the first human infection with [HPAI (H5N1)] acquired from contact with infected cattle and the second confirmed human case of influenza A(H5N1) detected in the country. No additional associated cases of human infection with influenza A(H5N1) have been identified. Since the virus has not acquired mutations that facilitate transmission among humans and based on available information, WHO assesses the public health risk to the general population posed by this virus to be low and for occupationally exposed persons, the risk of infection is considered low-to-moderate.“ In addition, the American Association of Bovine Practitioners (AABP) now recommends a new name, Bovine Influenza A Virus (BIAV) because the virus is not highly pathogenic in dairy cows.

The WHO lists the following factual information about avian influenza: i) “Direct contact with infected animals (through handling, culling, slaughtering or processing) or indirect contact (through environments contaminated with bodily fluids from infected animals) represent a risk for human infection.“; ii) “animal influenza viruses are distinct from human influenza viruses and do not easily transmit to and among humans;” and iii) sustained person-to-person transmission is not demonstrated.

Of all the transmission sources reported in surveillance systems by CDC and other government agencies (animal contact, environmental, foodborne, person-to-person, and waterborne), the only demonstrated transmission source for HPAI transmission to humans is animal contact. In light of the body of evidence on HPAI transmission to humans by direct animal contact, not by foodborne transmission, risk communications to avoid consumption of raw milk and raw milk products do not appear to be based on scientific evidence, but on other factors.

An earlier risk assessment conducted by FDA and USDA (2010) determined that HPAI “is not considered to be a foodborne pathogen although virus had been isolated from poultry muscle and the interior of eggs”. This is consistent with current facts compiled by the WHO about avian influenza transmission to date: i) “Direct contact with infected animals (through handling, culling, slaughtering or processing) or indirect contact (through environments contaminated with bodily fluids from infected animals) represent a risk for human infection.“; ii) “animal influenza viruses are distinct from human influenza viruses and do not easily transmit to and among humans;” and iii) “sustained person-to-person transmission is not demonstrated”. Although HPAI was detected in milk from ill cows in TX, as in poultry muscle and eggs, no evidence supports foodborne transmission of HPAI to humans.

While no evidence supports milkborne or foodborne transmission of HPAI to humans, evidence does exist that demonstrates a multitude of well-characterized mechanistic factors that inactivate viruses and prevent foodborne illness. Key studies in the peer-reviewed literature are cited in brackets, with full references appended.

First, consider peer-reviewed studies demonstrating antiviral properties of a suite of bioactive components of raw mammalian milks, including bovine milk [4,5,7-9,12-14,16,17,19]. Multiple researchers note that some of the antiviral components of milk listed in the text box below are likely function synergistically, meaning effects are greater in combination than independently, an observation particularly relevant in complex gut ecosystems of humans that include innate and adaptive immune systems. Many of these bioactive components of raw milk are also sensitive to heat and may be absent, inactive, or present in lower concentrations in pasteurized milks. Considering the extensive literature on antiviral activity in milk, clinical researchers [3] applied deep scientific knowledge to recommend that infants not be deprived of raw breastmilk due to the presence of viruses. The benefits of feeding raw breastmilk including its antiviral components to infants outweighs the very small risk of infection, from their perspective as clinical researchers, one associated with the Italian Association of Human Milk Banks.

Next, consider the gauntlet of defenses against foodborne pathogens in the human digestive tract [1,6,18]. These defenses include physical (stomach acidity, peristalsis), chemical (digestive enzymes), and cellular (innate and adaptive immune system, microbiota) factors that, acting simultaneously or sequentially, inactivate pathogens, including viruses, and/or suppress infectivity and virulence of ingested pathogens. Researchers [11] note that HPAI is an enveloped virus, susceptible to disruption and degradation in stomach acids, unlike the 16 viruses known to be transmitted to human by the oral route [6]. Further, FDA and USDA determined in 2010 that HPAI “is not considered to be a foodborne pathogen” even though virus was isolated from poultry muscle and the interior of eggs.

Host chemical and cellular defenses include:  complement; defensins; enzymes; interferons; interleukins; pattern recognition receptors (Toll-like receptors 3, 4, and 7; NOD-like receptors; RIG-1 receptors); and an array of host cells (dendritic cells, B cells, intestinal epithelial cells, macrophages, monocytes, natural killer cells, T cells) and cells of the gut-associated microbes or microbiota. Also, the gut microbiota include not only commensal (non-pathogenic) bacteria, but also commensal viruses that can modulate infectivity and virulence of pathogens [10].

Now, consider that the microbial ecology of raw milks including antiviral activity as described briefly above aligns with recent CDC data for all transmission sources from 2005 to 2020 [15]. This CDC dataset included 3,807 milkborne illnesses (2,111 associated with pasteurized milk) linked to bacterial pathogens, but lacks any viral illness associated with milk, raw or pasteurized. The predominant virus in this CDC dataset was norovirus, associated with 8,199 illnesses from leafy greens reported over this 16-year period. No norovirus illnesses or any other viral illnesses were reported in milk.

What is known about HPAI transmission to humans is that it is rare, requiring prolonged direct contact with infected, sick, and dead animals, generally birds, now dairy cows, that can lead to mild flu-like symptoms or eye inflammation, some progressing to fatal infections, according to WHO. Again, HPAI in humans is linked to transmission via animal contact, not by foods.

It seems that occupational exposure resulted in infection of a farm worker handling ill cows, with developed of one symptom in the worker, eye redness (conjunctivitis), consistent with transmission by animal contact. HPAI has been detected in dairy cows in Texas, Kansas, New Mexico and Michigan as of April 2. The dairy animals and rare humans affected have recovered.

Cross-disciplinary evidence demonstrates that raw milk from healthy cows is not inherently dangerous, consistent with the CDC evidence of trends for 2005-2020 [15] and evidence of benefits and risks [2]. There is no scientific evidence that HPAI in raw milk causes human disease.

Please consider the references below and pose questions in the comments. Also stay tuned for my next blogs on our recent peer-reviewed publications.

• Trends in burdens of disease by transmission source (usa, 2005–2020) and hazard identification for foods: focus on milkborne disease.
  Journal of Epidemiology and Global Health.

• Suppression of pathogens in properly refrigerated raw milk.
  PLOS ONE

• Lessons identified from applications of the Risk Analysis Quality Test Release 1.0.
  Risk Analysis

References

1.           Buchanan RL, Havelaar AH, Smith MA, Whiting RC, Julien E. The key events dose-response framework: its potential for application to foodborne pathogenic microorganisms. Critical Reviews in Food Science and Nutrition. 2009 Sep 22;49(8):718-28.

2.           Dietert RR, Coleman ME, North DW, Stephenson MM. Nourishing the human holobiont to reduce the risk of non-communicable diseases: a cow’s milk evidence map example. Applied Microbiology. 2021 Dec 30;2(1):25-52.

3.           Francese R, Peila C, Donalisio M, Lamberti C, Cirrincione S, Colombi N, Tonetto P, Cavallarin L, Bertino E, Moro GE, Coscia A. Viruses and human milk: transmission or protection?. Advances in Nutrition. 2023 Aug 20.

4.           Gallo V, Giansanti F, Arienzo A, Antonini G. Antiviral properties of whey proteins and their activity against SARS-CoV-2 infection. Journal of Functional Foods. 2022 Feb 1;89:104932.

5.           Gallo V, Arienzo A, Tomassetti F, Antonini G. Milk bioactive compounds and gut microbiota modulation: the role of whey proteins and milk oligosaccharides. Foods. 2024 Mar 16;13(6):907.

6.           Lockhart A, Mucida D, Parsa R. Immunity to enteric viruses. Immunity. 2022 May 10;55(5):800-18.

7.           Kaplan M, Şahutoğlu AS, Sarıtaş S, Duman H, Arslan A, Pekdemir B, Karav S. Role of milk glycome in prevention, treatment, and recovery of COVID-19. Frontiers in Nutrition. 2022 Nov 8;9:1033779.

8.           Oda H, Kolawole AO, Mirabelli C, Wakabayashi H, Tanaka M, Yamauchi K, Abe F, Wobus CE. Antiviral effects of bovine lactoferrin on human norovirus. Biochemistry and Cell Biology. 2021;99(1):166-72.

9.           Panon G, Tache S, Labie C. Antiviral substances in raw bovine milk active against bovine rotavirus and coronavirus. Journal of Food Protection. 1987 Oct 1;50(10):862-7.

10.         Pavia G, Marascio N, Matera G, Quirino A. Does the human gut virome contribute to host health or disease?. Viruses. 2023 Nov 17;15(11):2271.

11.         Sangsiriwut K, Uiprasertkul M, Payungporn S, Auewarakul P, Ungchusak K, Chantratita W, Puthavathana P. Complete Genomic Sequences of Highly Pathogenic H5N1 Avian Influenza Viruses Obtained Directly from Human Autopsy Specimens. Microbiol Resour Announc. 2018. 7(22):e01498-18. doi: 10.1128/MRA.01498-18. PMID: 30533850; PMCID: PMC6284082.

12.         Santos I, Silva M, Grácio M, Pedroso L, Lima A. Milk antiviral proteins and derived peptides against zoonoses. International Journal of Molecular Sciences. 2024. 25(3):1842.

13.         Schlusselhuber M, Godard J, Sebban M, Bernay B, Garon D, Seguin V, Oulyadi H, Desmasures N. Characterization of milkisin, a novel lipopeptide with antimicrobial properties produced by Pseudomonas sp. UCMA 17988 isolated from bovine raw milk. Frontiers in Microbiology. 2018. 9:355822.

14.         Singh P, Hernandez‐Rauda R, Peña‐Rodas O. Preventative and therapeutic potential of animal milk components against COVID‐19: A comprehensive review. Food Science & Nutrition. 2023. 11(6):2547-79.

15.         Stephenson MM, Coleman ME, Azzolina NA. Trends in burdens of disease by transmission source (USA, 2005–2020) and hazard identification for foods: focus on milkborne disease. Journal of Epidemiology and Global Health. 2024 Mar 28:1-30.

16.         Tache S, Benkaddour M, Corpet DE. Rotavirus inhibitor and recovery in raw bovine milk. Journal of Food Protection. 1995 Apr 1;58(4):434-8.

17.         Taha SH, Mehrez MA, Sitohy MZ, Abou Dawood AG, Abd-El Hamid MM, Kilany WH. Effectiveness of esterified whey proteins fractions against Egyptian Lethal Avian Influenza A (H5N1). Virology Journal. 2010 Dec;7:1-4.

18.         Wan T, Wang Y, He K, Zhu S. Microbial sensing in the intestine. Protein & Cell. 2023 Nov 1;14(11):824-60.

19.         Wang X, Yue L, Dang L, Yang J, Chen Z, Wang X, Shu J, Li Z. Role of sialylated glycans on bovine lactoferrin against influenza virus. Glycoconjugate Journal. 2021 Dec 1:1-8.

I partnered with colleagues of the Society for Risk Analysis (SRA) Applied Risk Management (ARM) specialty group this year to organize a round table panel symposium and workshop on the Risk Analysis Quality Test (RAQT) and applications of the RAQT tool to historic microbial risk assessments.

The RAQT is a battery of 76 Analysis Quality Tests (AQTs) for evaluation of quality, full disclosure, and shortfalls of risk analyses.

The RAQT was developed by an international team of SRA risk practitioners and leaders from diverse disciplines. The goals of the RAQT are:

1. providing a yardstick for measuring quality of data, analysis, process

2. providing full disclosure on assumptions and impacts

3. considering opportunities to improve and update past, current, and future assessments

4. creating a culture of quality analysis in SRA and the wider world

Interested in learning more about the RAQT and some applications?

Join us on Sunday, December 4th at the Tampa Waterside Marriott in Tampa FL for SRA Workshop # 6 entitled Risk Analysis Quality Test (RAQT) & Applications to Improve Risk Analyses & Risk Management Decisions.

Consider these questions:

1. Are you confident that technical risk analysis you conduct informs risk management decisions as you believe it ought to?

2. Are you confident you know what changes could most improve your risk analysis practices and how to demonstrate the value of those changes?

3. Do you feel it is acceptable for people to suffer harm due to ineffective or biased risk assessment with insufficient communications about quality of analysis to risk managers and the public?

If you answer “no” to any of these questions, then this workshop is for you!

The workshop offers:

• An overview of the purpose for, development of, and the questions comprising the Risk Analysis Quality Test (RAQT);

• Prototypical example applications of the RAQT to microbial risk assessments; and

• Group discussions of challenges and opportunities in applying the RAQT.

Presenters:

Applied Risk Management Specialty Group Leaders

• John Lathrop, Past Chair ARM SG, Decision Strategies

• Robert Waller, Chair-Elect ARM SG

Food Microbiologists/Risk Assessors

• Peg Coleman, SRA Councilor, Coleman Scientific Consulting

• Tom Ross, University of Tasmania, Australia

You will acquire:

• An overall understanding of SRA’s Risk Analysis Quality Test (RAQT)

• Ideas for how you can use the RAQT to evaluate:

o your own work;

o planning for a future risk analysis project; and

o areas for improvement in past projects or ongoing processes.

register and You can join in deliberations about these two government assessments.

Advance registration by November 1st is required.

The fees for the half-day workshop (1 - 5 pm) are only $35 for students and $225 for SRA members and non-members.

Share our workshop flyer with others!

Do you have some questions?

Click on the name of any of the workshop organizers to contact them by email.

• John Lathrop, Past Chair ARM SG, Decision Strategies

• Robert Waller, Chair-Elect ARM SG

• Peg Coleman, SRA Councilor, Coleman Scientific Consulting

See you in Tampa!

Such partnerships between these inter-disciplinary organizations could provide synergy for more effectively supporting holistic, integrated, long-term efforts to revitalize and transform neighborhoods that have suffered from decades of disinvestment. The webinar began with a comprehensive presentation on Purpose Built and Blueprint 15 leaders in the first hour, followed by 20 minutes of dialogue exploring potential partnerships with SRA leaders.

The panelists from Purpose Built include the following leaders. Click on their names for their LinkedIn profiles.

• Ginneh Baugh, Vice President of Impact and Innovation at Purpose Built Communities;

• Ashley Bozarth, Knowledge Manager at Purpose Built Communities; and

• Raquan Pride-Green, Executive Director of Blueprint 15, the ‘community quarterback’ organization of Purpose Built located in Syracuse, NY.

In addition, SRA leaders joined the discussion. Again, click on their names for their LinkedIn profiles.

• Peg Coleman, Upstate NY SRA President, moderator;

• Phil Goodrum, principal toxicologist, GSI Environmental Incorporated, visiting adjunct professor, SUNY ESF, Upstate NY SRA member;

• Mary O’Reilly, adjunct assistant professor, University Albany, Upstate NY SRA member; and

• Robyn Wilson, professor of risk analysis and decision science, Ohio State University, Past-President of SRA.

Click in the image below to view the recording of the webinar.

For a brief introduction, Purpose Built was founded in 2009 to replicate a new model for community re-development based on successes in the East Lake neighborhood in Atlanta. Click on this link for more information about the current network of 28 ‘community quarterback’ organizations working at locations illustrated in the figure below, including Blueprint 15 as the first Network Member in NY state.

The 2019 report on the 10th anniversary of Purpose Built Communities provides a review of the science and research that impacts work to date. The review lamented ineffective ‘silo reforms’ and noted the error of the assumption that 'the world is governed by simple cause-and-effect, highly linear relationships' (page 13 of the review). Some discussion explored how SRA risk practitioners, regional organizations, and specialty groups might help facilitate development of emergent strategies and models considering spatial interdependence to replace overly simplistic 'solutions'.

The SRA webinar discussion focused on gaps identified within and between communities, particularly needs for collecting data and translating often complex data for effective dialogue with neighborhood residents. One SRA member highlighted Paul Slovic’s work and the importance of ‘telling the story’ in terms that residents can relate to rather than presenting typical outputs of risk assessments that are not easily communicated to the public. The transformations of communities are viewed as long-term projects, perhaps exceeding10 years, with periodic updating of needs assessment and data collection needs over time.

Three SRA Specialty Groups in particular were mentioned in the discussion as providing very relevant expertise: Risk Communication, Justice Equity and Risk, Occupational Health and Safety. Also mentioned was the importance of considering both work and home environments, as described in the NIOSH Total Worker Health Program.

Upstate NY SRA members look forward to continuing conversations with Blueprint 15 leaders and other partners in Syracuse, including SUNY College of Environmental Science and Forestry (SUNY ESF) faculty, staff, and alumni.

Interested in exploring partnerships in Syracuse and beyond?

Contact Peg Coleman to connect with Upstate NY SRA and the Racial Equity Committee of the ESF Alumni Association, Ashly Bozarth to connect with Purpose Built, and Raquan Pride-Green to connect with Blueprint 15.

1. 2021a: Coleman, M.E., North, D.W., Dietert, R.R., Stephenson, M.M. Examining Evidence of Benefits and Risks for Pasteurizing Donor Breastmilk. Applied Microbiology 1(3):408-425. {Approximately 700 views since publication in September}

2. 2021b: Coleman, M.E., Dietert, R.R., North, D.W., Stephenson, M.M. Enhancing Human Superorganism Ecosystem Resilience by Holistically ‘Managing Our Microbes’. Applied Microbiology. 1(3): 471-497. {Approximately 600 views since publication in October}

3. 2022. Dietert, R.R., Coleman, M.E., North, D.W., Stephenson, M.M. Nourishing the Human Holobiont to Reduce the Risk of Non-Communicable Diseases: A Cow’s Milk Evidence Map Example. Applied Microbiology. 2(1):25-52.

The most recent publication above is a companion manuscript to the breastmilk evidence map below that was published in September (Coleman et al., 2021a). Now you can consider maps of the scientific evidence for benefits and risks for fresh unprocessed (raw) and pasteurized mammalian milks, breastmilk and cow milk. You many not have realized that most human milk banks in the US and around the world PASTEURIZE donor breastmilk before providing it to sick or premature infants in neonatal intensive care units (NICUs) whose mothers are unable to breastfeed. You may also not realize that multiple clinical studies around the world demonstrate significant loss of benefits of feeding pasteurized donor milk to NICU infants rather than raw donor milk. The evidence map papers document the body of evidence and uncertainties.

The third invited manuscript considers examples where evidence exits for managing disease by managing our microbes, using Microbiome First Medicine (medical research focused first on the human superorganism majority, the microbiome) in exploring holistic sustainable health care. This is in stark contrast to the traditional medicine focus on pharmaceuticals tested only on the human superorganism minority, Homo sapiens, in the words of co-author and Cornell University Emeritus Professor of Immunotoxicology Rodney Dietert. If this puzzles you, a must-read is Rodney’s book, The Human Superorganism, that provides persuasive evidence that human genes represent the minority for Homo sapiens incomplete without microbial partners in health. Thus, much of the variability in the frequency and magnitudes of benefits and risks associated with human superorganisms is likely associated with our microbial partners. Yet, typical frameworks for risk assessment exclude the microbiota.

In summary, these three invited peer-reviewed manuscripts introduce evidence mapping as a tool to provide clear, coherent descriptions of the complexities on the ‘state of the science’ for human superorganisms, as well as the uncertainties, for health and for both infectious and non-communicable diseases. The interconnectedness of human superorganisms reach beyond single organ systems including the gut, neural, and respiratory systems, now described as the gut-lung-brain axis. Research in systems ecology and Risk Analysis incorporating the microbiome can contribute to design of key studies testing for causality of effects that go beyond measuring correlations, but enable quantitative or qualitative predictions of the key microbial consortia needed to support health. Such studies are essential for filling knowledge gaps that at present limit broader transdisciplinary applications to support evidence-based decision making, holistic risk management, and design of microbiota-based preventative and therapeutic strategies to holistically ‘manage our microbes’.

I acknowledge the support of many of you readers who contributed to the crowdfunding campaign in 2018 that provided partial funding for this work. A thousand thanks.

Feel free to post comments and questions or email me. Happy New Year in 2022 and beyond for all you human superorganisms!

The one point that I disagree with in the whole article is that 'consuming raw milk is indeed more dangerous than consuming pasteurized milk'. Yet the FDA and my former employer FSIS determined in a 2003 QMRA [quantitative microbial risk assessment] that raw milk and pasteurized milk were BOTH high risk foods linked to listeriosis.

Listeriosis deaths were documented in the US and Canada from pasteurized milk and ice cream made from it in recent years. When were the last deaths attributed to consuming raw milk documented in the US and Canada? When were the last deaths attributed to raw milk in an individual without significant co-morbidities? Were any deaths attributed to children since the days of ‘swill milk’? Check out these peer-reviewed papers.

• Condran and Crimmins, 1980. Mortality differentials between rural and urban areas of states in the northeastern United States 1890–1900.

• Crimmins and Condran, 1983. Mortality variation in US cities in 1900: a two-level explanation by cause of death and underlying factors.

• Eagan, 2005. Organizing protest in the changing city: Swill milk and social activism in New York city, 1842–1864.

• Obladen, 2014. From swill milk to certified milk: progress in cow's milk quality in the 19th century.

• Alsan and Golden, 2019. Watersheds in Child Mortality: The Role of Effective Water and Sewerage Infrastructure, 1880 to 1920.

• Feigenbaum et al., 2019. Regional and racial inequality in infectious disease mortality in US cities, 1900–1948.

Robert Wright is right on point with his next observations. 'Like so much government disinformation, that claim [that 'raw milk can contain a wide variety of harmful bacteria'] is only partially correct. Bovine milk can become contaminated with anything after it leaves the cow’s udder due to unclean milking or handling processes but to suggest that milk from healthy cattle naturally teems with such nasties is disingenuous.'

The FDA claim is also NOT supported by a huge and expanding body of evidence characterizing the natural microbiota of milk. Consider these studies.

• Breitenwieser et al., 2020. Complementary Use of Cultivation and High-Throughput Amplicon Sequencing Reveals High Biodiversity Within Raw Milk Microbiota.

• Oikonomou et al., 2020. Milk microbiota: what are we exactly talking about?

• Wu et al., 2019. Rumen fluid, feces, milk, water, feed, airborne dust, and bedding microbiota in dairy farms managed by automatic milking systems.

No food is risk-free, but the FDA certainly does appear to be 'disingenuous' at best in its campaign against raw milk. Robert Wright later states that 'paternalistic governments banned raw milk, as if it was a really dangerous substance, like cigarette tobacco.' The closing paragraph of this article sums it up nicely.

'Americans don’t need government officials telling them what to do and what not to do. They do need clear, honest data and risk assessments unbiased by profit or ideological motives. The government, however, increasingly appears incapable of providing even that, even when it comes to foundational needs like nutrition.'

Is it time to update the QMRAs [quantitative microbial risk assessments] to consider data from the 21st century and objectively assess risk with attendant uncertainties for raw and pasteurized milks for Listeria monocytogenes and all the foodborne pathogens that are feared to be present in raw milk?

Is it time to update the evidence supporting and challenging the need for an interstate ban on raw milk, raw butter, and raw kefir that are NOT causing deaths in the US when modern raw milk producers apply Hazard Analysis and Critical Control Point (HACCP) programs or Risk Analysis and Management Plans (RAMPs) to minimize risks, consistent with training for dairy farmers listed with Raw Milk Institute?

What costs and benefits are associated with the 1947 mandate for pasteurization and the 1973 ban on interstate shipment of raw milk? Who benefits? Seems to me, neither family farms nor consumers benefit, and costs to public health include the pandemic of allergies, asthma, and inflammatory diseases associated with pasteurized and perhaps ultra-pasteurized and boiled milks.

I am curious to hear from another economically-minded colleague, former FDA risk analyst Richard Williams, and from my colleague Mark McAfee of the Raw Milk Institute mentioned in the AIER article, about their perspectives on this article by Robert Wright and my commentary.

I never imagined that I would be preparing a 5th blog on a viral pandemic this year, but I believe that risk practitioners have great value to contribute to deliberations of how to assess and communicate risks and benefits, and manage risk tradeoffs, in these difficult, uncertain times. Kudos to those experts from the Society for Risk Analysis (SRA) who are contributing critical interdisciplinary perspectives that are sorely needed to develop appropriate tradeoffs for health and economic and social risks that communities, nations, and the world are suffering as the COVID-19 pandemic caused by the novel corona virus SARS-CoV-2 illustrated below continues to spread around the world.

This blog covers experiences applying the Reopening NY Sports and Recreation Guidelines to minimize risks, new studies on inactivation of the novel corona virus (SARS-CoV-2) by simulated sunlight and a comprehensive Quantitative Microbial Risk Assessment (QMRA) for indoor and outdoor exposures to viral aerosols, and podcasts from more episodes of the SRA COVID Conversations on Risk series.

Some Issues on Reopening Outdoor Sports

Even people who know me may not know that I work out with the Ithaca Dragon Boat Club (IDBC) here in beautiful upstate NY. IDBC members practice Monday, Wednesday, and Saturday on the longest and second deepest of NY’s Finger Lakes (Cayuga Lake, ~40 miles long).

For the first two months this year, members paddled kayaks and canoes, not our dragon boats. If you have not seen a dragon boat or a race, the risks may not be obvious. Here is a photo of the IDBC competing in a boat at last year’s Chatauqua Lake Dragon Boat Race, and another of the medal brought home by each of the 22 team members.

After you view the photo below, the risks are obvious. A full dragon boat has 20 paddlers in 10 pairs, cheek to cheek, plus a drummer and a person to steer. So, a team of 22 people in close contact, breathing hard, some mouth breathing, would assume some risks without making adjustments for COVID-19.

Our boats are docked outdoors in an Ithaca City Park, and all users of Ithaca City and NY State Parks, including IDBC members, wear masks or face shields to protect themselves and others when the six-foot social distancing limit cannot be maintained. So, no races and no medals like this one from the Chatauqua Lake race are likely for the 2020 season.

IDBC now has procedures specifying the adjustments we are making for COVID-19 this season, as well as a NY Forward Safety Plan. Any member who has symptoms or traveled within 14 days prior does not practice. Travelers outside of largely rural Tompkins County in upstate NY (where <200 residents tested positive and none have died during the pandemic so far) can return to practice after 14 days of symptom-free quarantine.

The IDBC’s two new boats, the Osprey and the Taughannock, left the dock for the first time this weekend with masked paddlers. Members signed up in advance on the Team App for an assigned seat on a dragon boat, with one member steering. Other members continued to paddle individually, in kayaks, canoes, outrigger canoes, and stand up paddleboards (SUPs). IDBC is committed to following these guidelines and procedures to protect our health and the health of our community.

Where’s the Science? The Risk Analysis?

This week, I shared two newly published studies with IDBC members that are relevant to our practices.

• Simulated Sunlight Rapidly Inactivates SARS-CoV-2 on Surfaces (Ratnesar-Shumate et al., 2020)

• Infection Risk Assessment of COVID-19 through Aerosol Transmission: a Case Study of South China Seafood Market (Zhang et al., 2020)

The first study, conducted by researchers at the National Biodefense Analysis and Countermeasures Center (NBACC) in MD, found that 90% of the novel corona virus in simulated saliva (mimicking respiratory droplets) was inactivated within 7 minutes in simulated sunlight. Thus, IDBC leaders consider that disinfection of the boats between practices is not warranted at present. However, disinfectant is provided if paddlers prefer extra protection. Paddlers will not share water bottles, paddles, or life preservers, and will be assigned, one per seat, on alternate sides of the boat for proper balance while minimizing potential exposures via physical contact and exhaled air.

The second study was shared with me by SRA Fellow and Drexel University Professor Charles Haas. Zhang and colleagues integrated available data on SARS-CoV-2 (or data on related corona viruses as potential surrogates) and made assumptions to model hypothetical risk scenarios for potential transmissions at the Wuhan South China Seafood Market.

For example, although data on viral shedding from infected persons and aerosol transmission are not available from the market early in the pandemic, laboratory data on viral replication in tissue culture cells was used to estimate the potential load of viral shedding from an infected worker. Detailed models were developed to simulate potential dispersion of virus from one infected worker through indoor air with models for biologic decay, lung deposition for those inhaling contaminated air, and infection of others working or shopping in this specific indoor environment with minimal ventilation. Further, potential dispersion of contaminated air exiting the building into outdoor air was modeled for various distances outside the exits of the building. The simulation approach and results are illustrated below.

The dispersion model predicted that contaminated air exiting the building by natural ventilation is rapidly diluted, with dispersion into high altitudes well outside the breathing zone of simulated pedestrians as distance increased from the exits of the market. Risk estimates decreased by 100-fold for pedestrians 600 meters away from the market, relative to someone at the exit before dispersion of contaminated air. The predominant uncertainties noted by the researchers were the models for estimating likelihood of illness at inhaled viral doses or viral loads (dose-response modeling), viral shedding from infected persons, and biological decay (e.g., desiccation and inactivation via multiple factors).

What We Don’t Know

From these studies and other evidence discussed by SRA experts in the COVID Conversations on Risk series, we do not know:

• what viral doses (viral loads) in the exhaled breath, sneezes or coughs of an infected person are necessary before that person sheds virus and becomes infectious to others;

• what viral doses (viral loads) are necessary for inhalation, infection, and progression to illness in persons with variable susceptibility factors; and

• how likely such viral doses are within the breathing zone of dragon boat paddlers sitting on average 4.5 feet apart (or even 6 feet apart) under variable outdoor conditions of sun, wind, rain, and spray.

What Do SRA Experts Have to Say?

Click on the link below to view the 1-hour podcast of Episode 9 of the SRA COVID Conversations on Risk series, considering aerosol transmission and implications for public health. The speakers are two esteemed SRA Fellows, both recipients of the SRA Presidential Recognition Award: Drs. Elizabeth Anderson of Exponent and Charles Haas of Drexel University. Dr. Anderson is a Past President of SRA and RJ Burk Outstanding Service Award recipient. Dr. Haas serves as area editor for Microbial Risk Assessment for the SRA journal Risk Analysis.

Dr. Anderson shared this review published in Annals of Internal Medicine that includes summaries of the available evidence on asymptomatic transmission.

• Prevalence of Asymptomatic SARS-CoV-2 Infection : A Narrative Review (Oran and Topol, 2020)

Click on the link below to listen to the 30-minute podcast of Episode 10 of the SRA COVID Conversations on Risk series, on compound hazards (pandemic and floods, fires, hurricanes) by Drs. Robyn Wilson of The Ohio State University and Gina Eosco of the National Oceanic and Atmospheric Administration. Dr. Wilson is a recipient of the Chauncey Starr Distinguished Young Analyst Award. Dr. Eosco is another distinguished young analyst who spoke at an Upstate NY SRA event while she was a student at nearby Cornell University, studying with former SRA President Katherine McComas.

Thank you to these SRA experts and all those who contribute to COVID Conversations on Risk.

Bottom Line: WEAR YOUR MASK!

Uncertainties still exist, even in areas where the rates of new cases seem to be declining. Since we cannot predict who may be infectious in a crowd, whether or not they tested positive or have symptoms, protect yourself and others by masking and complying with guidance as our communities work their way back to full recovery.

NOT SURE YOU BELIEVE CLOTH MASKS ARE EFFECTIVE?

Dr. Rich Davis, Director of the Microbiology Lab at Providence Health Care, demonstrated that a simple cloth surgical style mask is effective at blocking most respiratory droplets relevant to spread of COVID-19. Although viral particles may be dispersed farther than the bacteria cultured on the plates in Dr. Davis’s experiment, his results demonstrate a point made during the COVID Conversations on Risk webinar above by Dr. Haas: masks do not need to be perfect (e.g., N95 respirator with very close facial fit and very efficient filtration of airborne particles) to physically trap microbes in exhaled air from talking, singing, coughing, and sneezing. Growth is obviously higher after coughing and sneezing than talking or singing, consistent with higher risk of COVID transmission for those exposed to coughing and sneezing of symptomatic cases.

WEAR A MASK to reduce risks to yourself and others around you.

Calling pregnant women and breastfeeding moms

If you’ve tested positive for SARS-CoV-2 and are pregnant or breastfeeding, particularly those living in NY City, you have a unique opportunity to contribute to a year-long study examining whether antibodies in breastmilk can protect babies and perhaps adults from the novel corona virus. Contact immunologist Rebecca Powell here for more information. Also see the recent study including Dr. Powell on antibodies in breast milk following recovery from COVID-19 (Fox et al., 2020).

What do we know about transmission of SARS-CoV-2 in breastmilk?

As illustrated below, available evidence suggests the virus is NOT transmitted to babies from breastmilk of positive mothers, BUT antibodies to the virus ARE TRANSMITTED!

A systematic review ( Liguoro et al., 2020) provides additional information from mothers around the globe and their children (7,480 children 18 years old or younger).

The most common symptoms for pediatric cases were fever, cough, and sore throat. Most newborns were asymptomatic or had mild or moderate illness.

The review does NOT mention rash, a symptom that has been recently hypothesized as potentially associated with the pandemic.

The conclusion of the review: COVID-19 affects children less severely than adults.

The review included 62 studies and three previously published reviews.

Consider the figure below from one of the studies cited in the systematic review (Han et al., 2020) conducted in Korea.

Why is this figure relevant?

It illustrates a problem with biological data from clinical samples: limits of the methods to detect and quantify levels of the virus over time. Symbols plotted below the dashed lines represent samples that would be reported as negative, but a negative sample is NOT necessarily free of viruses. Samples containing 1,000 virus particle per mL of sample could be classified as negative because the method is too unreliable to quantify counts precisely at lower levels.

What is clear is that even for neonates who are expected to be highly susceptible to many pathogens, viral load for this study declines steadily over time until non-detectable (e.g., below that dashed line for the threshold of reliable method performance). One exception might be stool, however documentation was not provided that this study identified viable infectious virus or just snips of RNA from degraded and non-infectious virus particles excreted in feces.

Episode 5 of SRA COVID Conversations on Risk

SRA President Seth Guikema interviewed Professor Emmanuel de-Graft Johnson Owusu-Ansah of Kwame Nkrumah University of Science and Technology Ghana and Professor Tyler Davis of Texas Tech in this hour-long webinar episode.

A relevant quote (All models are wrong; some models are useful!) points to the problems of modeling with limited data. Our assumptions that bridge current gaps in the data for assessing risk may be proven wrong as more evidence accumulates.

Next, we consider how risk communications influence perceptions and behavior amidst the challenges of the pandemic.

Click below to watch the video recording of the webinar.

Insights into Opening the Economy

Professor Guikema next interviewed two esteemed economists, Past SRA President Robin Cantor and her colleague Dubravka Tosic. Listen to their 48-minute perspectives at this link.

Episode 7 of SRA COVID Conversations on Risk: Resilience

For this episode, Brett Burke of the SRA Secretariat interviewed SRA Fellow and recipient of the SRA Chauncey Starr, Outstanding Practitioner, and Distinguished Educator Awards, Dr. Igor Linkov of the US Army Corps of Engineers, currently on detail to FEMA, and Professor Tom Logan of University of Canterbury, New Zealand.

Want to learn more about community resilience and systems thinking in this and previous pandemics including Black Death in Venice and Ebola in Africa?

Interested in understanding how Kubler-Ross grief cycle and New Zealand’s “well being budget” influence resilience and recovery planning and opportunities to build 21st century community cohesion rather than try (in vain) to restore 20th century capacities and infrastructure post pandemic?

Know why density IS NOT the problem for high fatality rates (comparing NY City, Hong Kong, and SIngapore)?

Click on the video below for an hour packed with new insights.

Joint Proposals on Pandemic for SRA Meeting Dec 13-17 (virtual and in-person, Austin, TX)

I am pleased that a pair of joint symposia were proposed this week on the pandemic and dose-response, jointly sponsored by the SRA Dose-Response Specialty Group and the Microbial Risk Analysis Specialty Group. The first is a technical symposium considering the available date including a call for meta-data to researchers who published data on viral load from cohort studies through the Quantitative Microbial Risk Assessment (QMRA) Wiki. The second session is a round table panel symposium to expand discussion to include evidence for transmission from asymptomatic and symptomatic carriers early and late in the disease cycle. The invited panelists and co-chairs will prepare a perspectives article for submission to the SRA journal Risk Analysis based on presentations from the technical symposium and dialogue from the round table panel symposium.

Short descriptions of the proposed sessions, with authors, affiliations, titles, and abstracts, are provided at the links below.

1. Data and Models for Dose-Response Relationships for SARS-CoV-2

2. Dialogue on Data and Models for Dose-Response Relationships for SARS-CoV-2

SRA members and non-members will be able to participate in these sessions, with virtual participation options if travel to Austin is inadvisable.

Stay tuned for more highlights from the SRA COVID Conversations on Risk series and more details about the SRA meeting in December.

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]]>RISK ANALYSTS' PANDEMIC PERSPECTIVES FROM NEW ZEALAND, US, GHANAriskMargaret ColemanMon, 04 May 2020 22:55:50 +0000https://www.colemanscientific.org/blog/2020/5/4/more-lessons-learned-about-pandemic-risk5b4f8179c258b42e4fe82cb7:5b550f6470a6ad6dfd06946c:5eb089fb397ac92048456478UNDERSTANDING VIRAL LOAD, METHODS MEASURING IT, AND DIRECT AND INDIRECT TRANSMISSION FROM SRA RISK PRACTITIONERS

Before I introduce you to the fascinating perspectives of 3 more Society for Risk Analysis (SRA) risk practitioners in the COVID Conversations on Risk series, here are reminders about microbial dose-response principles explaining why viral load (estimated inhaled dose) is crucially important for recovering from the pandemic.

The higher the initial dose,

• the quicker you’ll get ill (shorter incubation period)

• the more likely you’ll get ill

• the more likely you’ll become severely ill if you have one or multiple co-morbidities

• the longer you’re likely infective to others (longer duration of viral shedding)

Also, if your medical professionals are measuring your initial viral load, they’ll have more information about how quickly you might need specialized care to stop viral replication and prevent uncontrolled inflammation in your lungs. However, the available evidence for modeling outcome from viral load over time in different clinical samples (saliva, nasal or throat swabs, blood, urine, feces) by the most commonly used method (RT-PCR) are fragmented, represent very small numbers of cases that may not be representative of future cases, and may be reported as qualitative (positive or negative), semi-quantitative (high, medium or low categories), or quantitative (e.g., numbers of viral copies per mL of sample or per sample) of different utility for risk assessment. For microbial risk assessors to develop predictive models to assist in communication and management of pandemic risks, higher quality data is needed for reliable dose-response assessment.

I hear many frustrations voiced about all the uncertainties around this pandemic. Here are some grave frustrations for the global community.

• This SARS-CoV-2 virus seems to replicate to higher levels early in the course of mild disease (e.g., at symptom onset) compared to related viruses that peaked a week or more after onset of symptoms severe enough to require medical intervention. The later peak likely provided some measure of protection limiting transmission for other viruses. Higher viral loads in people just starting to develop symptoms may contribute to higher rates of transmission and infection if social distancing and masking requirements are relaxed.

• People who test negative at one point in time for viral RNA in upper respiratory tract swab samples may be infected, but the most commonly used methodology (RT-PCR) cannot ensure absence of the virus in the body, particularly in the lower respiratory tract, the primary site of viral damage. One recent study (Wyllie et al., 2020) reported that their RT-PCR method would not detect less than 5,610 viral copies per mL sample fluid (<16,830 viral copies per 3-mL homogeneous sample volume). Two more recent studies reported on higher sensitivity methods using droplet digital PCR (ddPCR), one reportedly 500 times more sensitive (Suo et al., 2020), the other reported detecting from 10 to a million viral copies per test (Yu et al., 2020; see Figures from this study below). A third study (Patrone et al., 2020) reported improvements in sensitivity of RT-PCR by baseline corrections. Note that in addition to poor method sensitivity at low viral loads, false negatives could also reflect inconsistencies in swabbing efficiency or other sampling errors.

• Resources (time, expertise, costs of kits and reagents) are limited for testing huge populations around the world, and repeat testing limitations during recovery before discharge are likely to be just as critical as getting the initial round of testing completed in stopping the pandemic.

To illustrate the importance of using sensitive methods for quantitating viral load, figures from the Yu study below (Figures 3A, B, E) represent viral loads in 95 samples collected over time from 76 patients admitted to a Beijing hospital prior to February 19th. Samples were analyzed by the more sensitive ddPCR method. Chart A illustrates significantly higher viral loads in sputum compared to other types of samples (nasal and throat swabs, blood and urine). Chart B illustrates significant decline of viral load in sputum at three stages of disease progression. Chart E illustrates two special cases in convalescing patients with low level fluctuations in viral load from 10 to 150 viral copies per test for 9 days in the recovery stage before testing negative. Variability in duration of shedding and viral load may contribute to further transmission of the pandemic.

SRA COVID Conversations on Risk Series

I highly recommend two more podcasts from the SRA COVID Conversations on Risk series. The first is a 30-minute audio interview of Dr. Vicki Bier of University of Wisconsin by SRA President Seth Guikema. Dr. Bier is a Professor of Industrial and Systems Engineering and is recognized as an SRA Fellow and recipient of many awards, including the Distinguished Achievement Award and the Richard J. Burk Outstanding Service Award.

Professor Bier described lessons learned from previous pandemics and cautioned that people need to continue practicing social distancing as restrictions are relaxing. A concerning example for this pandemic was from the H1N1 pandemic. Although 65% of subway riders in Mexico City initially complied with advice from authorities to wear masks, ten days later only 10% of riders wore masks. Another lesson learned from the 1918 Spanish flu pandemic is that the consequences of relaxing restrictions too early are high, with greater economic and public health damages in Denver during the second peaks of illnesses and mortality.

So, the WHO advice (DoTheFive) is just as important to follow now that some local communities appear to be past the (first) peak. Protect yourself and others by wearing a mask so that together we prevent that second peak from happening in our communities.

Two more exceptional panelists offered their perspectives on Food Safety and Food Security in the pandemic, Drs. Jade Mitchell and Felicia Wu.

Dr. Mitchell is Assistant Professor of Biosystems and Agricultural Engineering at Michigan State University and currently serves as Chair of the SRA Microbial Risk Analysis Specialty Group.

Dr. Wu is John A. Hannah Distinguished Professor of Food Science and Human Nutrition and Professor of Agricultural, Food, and Resource Economics, also at Michigan State University. Professor Wu serves as the Area Editor of Health Risk Assessment for the SRA journal Risk Analysis, and has received numerous awards including SRA’s Chauncey Starr Distinguished Young Risk Analyst Award, and was selected (twice) as Society for Risk Analysis/Sigma Xi Distinguished Lecturer.

View the podcast of the hour-long webinar at the link below.

Food Safety Highlights

Fellow microbial risk assessor Dr. Mitchell illustrated how viruses spread by direct and indirect routes in this slide.

Dr. Mitchell also points out uncertainties about likelihood of transmission, notably that successful transmission depends on the dose inhaled being large enough to establish infection. No evidence exists, to our knowledge, documenting transmission and infection for SARS-CoV-2 that is attributable to contaminated surfaces. Rather, evidence points to direct person-to-person transmission via droplets (>5 microns) or bioaerosols (<5 microns) as most likely to transfer infective doses to others.

• Transmission by asymptomatic cases is theoretically possible, but not documented as a contributing path so far in this pandemic. Most cases are clustered as typical for person-to-person transmission from droplets or aerosols in the vicinity of ill people in families and households, workplaces, and community gatherings where social distancing controls have been lax.

• Indirect transmission from contaminated surfaces is theoretically possible, but not documented as a contributing path so far in this pandemic.

• Indirect transmission from stool positive for viral RNA is theoretically possible (fecal-oral route), but not documented as a contributing path so far in this pandemic.

Another slide from Dr. Mitchell discussed exposure parameters influencing estimates of risk, notably viral load. The figure from the study that Dr. Mitchell cites (Leung et al., 2020) merits a closer look.

The level of viral contamination in nasal and throat swabs from 17 symptomatic confirmed cases of SARS-CoV-2 ranged from undetectable to 10,000,000,000 viral copies per sample. The researchers also measured viral shedding in exhaled breath from 10 cases not wearing a face mask and 11 cases wearing face masks. Breath samples were collected within 72 hours of onset of illness. For this small study early in the course of disease, low viral loads were detected by RT-PCR after 30 minutes monitoring breath of 3 or 4 of 10 cases not wearing masks, and notably virus transmission was not detected for 11 cases wearing masks. Clearly, masks reduce exposures to symptomatic cases.

Dr. Mitchell closed with this slide conveying risk management strategies that are necessary (general strategies including social distancing) and some strategies (disinfecting food, packaging and rooms) that are likely unnecessary except for high risk groups.

Food Security Highlights

Professor Wu offered deep insights on food security and the complexities of determining a ‘social optimum’ for the appropriate level of system shutdown to balance public health and economic risks in this pandemic. Examples included health and economic risks to workers in production, processing, distribution, retail grocery, and restaurant sectors. Professor Wu discussed protests around what constitutes essential businesses. The pandemic has dramatically shifted focus on the most basic of needs from Maslow’s hierarchy, physiological needs, as illustrated in the screen shot below.

Further, Professor Wu described collaborative work (The Razor’s Edge of “Essential” Labor in Agriculture) submitted for publication in the journal Applied Economic Perspectives and Policy. Certainly, food is “essential” for life on this earth, and Professor Wu provided insights on risks to workers throughout the farm-to-fork supply chains now disrupted at frequency and scale previously unimagined. Actions to work around disruptions are being put in place, such as re-distributing foods such as shell eggs and onions contracted by restaurants to grocery stores and food banks.

Can we keep the food supply robust during this pandemic? Professor Wu offers potential solutions, near-term and long-term, to design resilient systems for food safety and security. A number of potential solutions highlighted by Professor Wu include sustained use of drive-through curbside pick-up and delivery options from grocery markets and restaurants, to hope for near term and long term solutions that stop the pandemic and optimize the balance during recovery between enhancing public heath and minimizing economic risks.

Food Safety and Security Questions

The webinar audience posed many insightful questions, including one posed by my readers after my first blog. Why is an obligate viral pathogen that cannot replicate in the environment outside a host cell such a concern for society as local communities begin to consider relaxing social distancing restrictions? The responses returned to uncertainties about direct and indirect transmission routes.

The more likely transmission route seems to be direct inhalation of droplets and bioaerosols released in close environments from unmasked, convalescent, and early stage cases that bear high viral loads. While it is theoretically possible that indirect transmission of viral loads high enough to cause illness occur via transfer from contaminated (and unsanitized) surfaces via hands to face, it is unclear that sufficient viral particles exhaled by unmasked, convalescent, and undetected early stage cases that dry out from deposited droplets are transmitted to cause pandemic disease.

While scientific data is presently lacking to inform assessment of the likelihood and magnitude of risk for indirect transmission via contaminated surfaces in public buildings, transmission to care givers treating severe cases is well documented. The extensive transmission to workers who cannot DoTheFive, including poorly protected workers in meat processing plants, grocery stores, restaurants and other businesses, could be due to direct person-to-person transmission and not via indirect transmission from bioaerosols or dried virus deposited on surfaces. More research is needed before ‘natural experiments’ are observed where relaxing restrictions results in second peaks of illness and death.  

Each risk practitioner featured in SRA COVID Conversations on Risk has reflected upon some silver linings, their hopes for enhancing safety and security of interconnected agricultural, economic, public health, and social systems as the pandemic subsides. More flexible and resilient systems offer future benefits to better balance priorities for public health, agriculture, economics, and social justice post-pandemic. As the world’s leading authority on risk science and its applications, SRA offers unique multi-/trans-disciplinary expertise and rigorous analytical perspective essential to synergistic teams who can effectively assess, communicate, and manage global risks incorporating uncertainty, ambiguity as knowledge advances, and complexities of our interdependent systems.

Local Community Responses

I am quite fortunate to live in beautiful rural upstate NY, in Tompkins County near Ithaca, where social distancing has been effective in limiting numbers of cases (129) and deaths (2) associated with the pandemic. The sobering statistics for other NY state counties are available on NYS-COVID19-Tracker and from NY City Health. Data by zip code is available from the latter site, as illustrated in the map below with cases as of May 6.

I am also fortunate to have compassionate and courageous neighbors, including Katrina who, along with her medical colleagues from Cayuga Medical Center and others, agreed to take a month of time away from our rural county to serve in Manhattan where 2,654 fatalities have occurred to date. NY State residents have suffered greatly, and most of the 19,415 deaths to date were reported in NY City, Long Island, and neighboring communities. Thankfully, no deaths were reported in persons under the age of 19 in this state. The sobering reality is that 84.4% of these deaths occurred in persons over age 60.

I cannot express in words how grateful I am that so many people around the world are battling COVID-19. Special thanks to Michele, a colleague and friend from Syracuse University, and others who have made fabric masks for family and friends. Insights on disruptions for workers are offered by another colleague at SU, Professor Ken Walsleben.

Although many communities are contemplating how and when to relax restrictions, the WHO message DoTheFive is crucially important to continue following. Let’s prevent the second wave and continue practicing social distancing for the greater social good.

Stay tuned for future episodes SRA COVID Conversations on Risk.

My previous post on the COVID-19 pandemic raised great questions from readers about lower severity of illness reported in areas outside hotspots or epicenters of the pandemic. The questions arose from the figure below from the World Health Organization on the dynamics of crude fatality ratios (CFRs) over space and time in China. CFRs steadily declined for the epicenter (Wuhan) from Jan 1st to Feb 10th. CFRs were considerably lower further from the epicenter.

One reader posed these three hypotheses besides identified risk factors (age, co-morbidities, and limitations of ICU beds or health care capacity). Severe cases might:

1. contact higher concentrations or titers of the virus in the hotspots (leading to higher inhaled doses or viral loads).

2. contract virus from multiple exposures or encounters with cases in hotspots (leading to cumulative doses and higher virulence than single doses).

3. are exposed to mutated, more virulent strains of the virus in hotspots.

Some data already exists to support one hypothesis, from my perspective as a longtime member of the Society for Risk Analysis (SRA) and a past president and current officer of the SRA Dose Response Specialty Group (DRSG). In a blog last fall, I described some of SRA’s specialty groups (SGs), and many of the 16 SGs have expertise to contribute to risk analysis for the pandemic. I will highlight DRSG here, but see appended list of the SGs with links to their websites and a contact person for broader perspectives of the deep and varried interdisciplinary expertise of SRA risk practitioners.

WHAT DO WE KNOW ABOUT DOSE-RESPONSE?

Assessing risk requires data on the doses of a hazard (for example, a chemical, physical hazard, or microbial pathogen like the novel corona virus) that cause illness or harm (adverse responses) in humans (or other organisms or the environment). DRSG members examine scientific data and generate dose-response models to predict the chance or likelihood of adverse responses and uncertainties associated with the response from the data available. Multiple studies on pandemic cases have already been published this year documenting groups of cases or cohorts admitted to hospitals. Most studies reported use of testing methods that are qualitative, reporting presence/absence of the virus from nasal swabs or nasopharyngeal swabs of the throat at the back of the nasal cavity. A few studies used quantitative methods that reported estimates of the viral loads (dose of virus) over the course of illness. These studies suggest that dose IS IMPORTANT in assessing and managing risk of pandemic illness.

Some general principles for describing dose-response relationships are illustrated in a recent study documenting dose-dependencies and time-dependencies for tularemia, a bacterial disease also associated with fever and flu-like symptoms in volunteers administered well-characterized aerosol doses of the pathogen (McClellan et al., 2017). As dose increases:

• the chance or likelihood of illness increases;

• the severity of illness increases; and

• the time before onset of symptoms decreases. (In other words, high doses make people sick sooner than low doses).

What was dramatically demonstrated in a hospital in Nanchang, China (Liu et al., 2020) is that these principles are consistent with emerging data quantifying the novel corona virus load estimated for a group of 76 cases. The estimated dose (initial viral load upon admission) was significantly correlated with severity of disease. Nasopharyngeal swabs were analyzed from 46 cases with mild illness and 30 cases with severe illness. Significantly higher mean viral loads were estimated for the 30 severe cases compared to those from the 46 mild cases (p<0.00001, Mann-Whitney test).

However, higher severity observed in local/regional hot spots with high densities of ill people could be due to the alternative hypotheses: 2) cumulative exposures to multiple repeated doses; or 3) mutation of the virus to higher virulence as it was transmitted from the epicenter of the pandemic.

Regarding the second hypothesis that multiple doses in hotspots cause more severe illness than single doses in more distant regions, I am not aware of definitive supporting evidence for corona viruses at present. It is reasonable to assume that exposures are more frequent near the epicenter. The statistical analysis documented in a recent study of repeated doses of a spore-forming bacterial pathogen (Coleman et al., 2017) may be relevant for designing experiments to test for effects of repeated doses of the novel corona virus in animal or tissue culture models. However, it also seems likely that care givers and medical professionals are exposed to higher doses and possibly repeated higher doses that may influence the likelihood and severity of disease, particularly if protective gear is not available or is not put on (and taken off) following guidance to minimize exposures.

Regarding the third hypothesis that the virus mutates to higher virulence in hotspots, I am not aware of definitive evidence for corona viruses at present. However, it seems unlikely at this point in study of this novel corona virus that higher fatality rates are linked to mutations in the virus based on a recent cohort study of mild and severe cases in Hong Kong (To et al., 2020) and this study on genomic variance (Ceraolo and Giorgi, 2020).

Other recent studies also extend knowledge for predicting the likelihood and severity of disease for the novel corona virus. A study conducted in Beijing (Yu et al., 2020) compared methods for qualitative (presence/absence) detection by reverse transcriptase polymerase chain reaction (RT-PCR) with quantitative estimation of viral load (droplet digital PCR or ddPCR) simultaneously for 95 cases over the full course of disease via samples from the upper and lower respiratory tract, blood, and urine.

Pan and colleagues (2020) reported results of viral loads in throat swabs and/or sputum (indicative of lower respiratory tract) from 82 cases in China, including serial samples of throat swabs, sputum, urine, and stool from 2 cases over the full course of illness and recovery by day 15. Variability in viral load was detected between specimens, with reporting of simple correlative analysis.

Two recent studies conducted in Germany provided the following new findings.

• Viral replication was limited to throat and lung, not blood, urine, and stool from 9 mild cases (Wolfel 2020)

• Person-to-person transmission efficiency appeared to decrease from the original index (primary) case to subsequent contacts (secondary and tertiary cases) in company and household clusters (Bohmer 2020)

I also encourage readers to take a look at this New Yorker article written by scientist and prize-winning author Siddhartha Mukherjee. (How Does the Coronavirus Behave Inside a Patient). The importance of understanding dose-response relationships was also noted by Dr. Mukherjee.

WHAT DON’T WE KNOW?

Great uncertainties remain, and multiple recent studies have identified crucial gaps in knowledge about SARS-CoV-2 that limit our ability for early identification of cases more likely to develop severe illness in order to reduce clinical severity and mortality. These studies (Huang et al., 2020; Joynt and Wu, 2020; Monteiro et al., 2020; Wong et al., 2020) point to critical knowledge gaps about detection, infectivity, and modes of transmission. Each of the gaps highlighted below are dependent on dose, either directly or indirectly.

• Dectection of the presence of viral RNA fragments in human clinical samples by PCR methods for one or two viral genes does not demonstrate replication or infectivity of the virus in that sample. For example, it is unclear if infective virus is present in stool or if the fecal-oral pathway is causing human illness in this pandemic.

• Feasible modes of transmission are poorly characterized. Transmission by aerosolized droplets and contact with cases are well documented for corona viruses, but the contribution of alternative modes of transmission (e.g., from asymptomatic cases, contact with surfaces, fecal-oral) is unknown.

• Potential biomarkers for disease severity are needed for early identification of cases more likely to progress to severe illness due to the broad clinical spectrum and non-specific initial symptoms. High initial dose early in disease onset seems a useful biomarker based on time series studies available.

WHY MIGHT DOSE MATTER?

Deeper understanding of the relationships between dose and likelihood, severity, and timing of adverse affects could support future evidence-based decisions about triage and therapeutic options. For example, quantitation of viral load would provide an early indicator of potential disease severity for allocation of limited supplies of convalescent serum to patients with high viral loads early in their disease cycle, prior to development of systemic potentially fatal complications.

The results of the Liu study are promising for supporting development of more rapid and streamlined triage procedures that could reduce the severity and mortality for future cases. While more data are needed to verify the results of the Liu study and generate a comprehensive statistically sound model predicting the magnitude and timing of adverse affects, the urgency of the need for biomarkers is extreme, considering the high fatality rates in major metropolitan areas around the world described below.

Expansion of the available data for dose-response assessment could lead to improvements in triage for new cases that reduce crude fatality ratios for the pandemic. Liu and colleagues noted that quantitation of viral load may be a useful biomarker for severe disease that could support early diagnosis for potential needs for ICU and critical care. If this study is generalizable to other populations around the world, medical staff could screen patients on admission for viral load, and those with high load might be provided additional therapeutics (e.g., convalescent serum) to more quickly reduce the viral load and lessen the severity of symptoms.

Can public health departments apply such quantitative methods tomorrow? Unlikely, without additional investment and training. Additional data are needed from hospitals and research organizations around the world for other cohorts of cases. The SRA community has the interdisciplinary/transdisciplinary expertise to assist in developing and communicating about reliable models to predict viral doses causing mild and severe disease for use in triage of cases with new or recurring infections. Tools to support earlier diagnosis of cases more likely to require ICU and critical care will be important to manage increasingly limited medical and testing resources in areas around the world where transmission to new cases has not yet dissipated.

PANDEMIC DYNAMICS AFTER MID-APRIL?

As of April 9th, the World Health Organization (WHO) Situation Report listed 1,436,198 confirmed cases from the pandemic, including 85,522 deaths (estimated overall crude fatality ratio approximately 6%). For the Region of the Americas, the report lists 454,710 confirmed cases and 14,775 deaths (estimated overall crude fatality ratio approximately 3%). The continuing toll on people’s lives plus on health care systems and on economic, financial, social, and religious structures is ‘certainly’ not good news, but knowledge is expanding. See the WHO Situation Report for guidelines for religious leaders and faith-based communities regarding the pandemic and other links to more detailed information.

The Corona Virus Resource Center at John’s Hopkins provides data and tools relevant to the pandemic, including data on numbers and rates of confirmed cases, hospitalizations, fatalities, and recoveries. The figure below was generated on April 17 using the Mortality Analyses tool.

One of the seven critical issues that require ‘concerted coordinated attention and action’ identified by Wong and colleagues (2020) from cases and responses in Singapore is relevant to SRA and the disciplines of analysis of risk perceptions and risk communications. The authors note that the ‘medical community needs to collectively find better ways to communicate and engage the public … understandably anxious’. How might these global needs be addressed? SRA is poised to fill this void through the COVID CONVERSATIONS ON RISK.

SRA’S FREE WEBINAR SERIES ON COVID CONVERSATIONS ON RISK

The magnitude of the pandemic prompted SRA leaders to organize a free a bi-weekly webinar series, COVID CONVERSATIONS ON RISK. The series will highlight diverse expertise that the SRA community can bring to bear on the difficult challenges of these trying and unusual times. In particular, multidisciplinary, risk-based perspectives are essential to address the complexities and uncertainties of the pandemic and help provide advice and guidance on evidence-based risk management actions.

On April 9th, SRA President Seth Guikema welcoming two internationally known panelists to this week’s webinar, interdisciplinary risk analyst Dr. Pia-Johanna Schweizer (Institute for Advanced Sustainability Studies, Potsdam, Germany) and Professor of Management Science Gilberto Monitbeller (Loughborough University, UK).

An extremely useful illustration was introduced by Dr. Schweizer, the ancient fable of the Blind Men and the Elephant, as applied to considering the pandemic as a systemic risk problem (see slide below). The fable has been viewed as a warning that partial perspectives of a whole (elephant, system, pandemic) may lead to mistaken images and overreaching interpretations of reality that could cause harm without openness to deliberation and analysis of the complexities.

For some SRA members, the warning of the fable could be interpreted as the need for exercise of Analytic-Deliberative Process (NRC, 1996, Understanding Risk: Informing Decisions in a Democratic Society) to build useful knowledge of the integrated whole, incorporating the different partial perceptions and other relevant data.

Analytic-Deliberative Process was described by a committee convened by the US National Academy of Sciences, the National Academy of Engineering, the Institute of Medicine, and the National Research Council as follows: characterization of 'a potentially hazardous situation in as accurate, thorough, and decision-relevant a manner as possible, addressing the significant concerns of the interested and affected parties, and to make this information understandable and accessible to public officials and to the parties' (stakeholders).

Clearly, we have never seen an ‘elephant’ like this pandemic, and the speakers describe successes, failures, and the need for significant improvements in Risk Communication and Risk Management from their perspectives of systemic risk and portifolio decision analysis.

I highly recommend that you click on the video below for COVID Conversations on Risk (Episode 1), a fascinating and challenging hour of dialogue with these exceptional analysts who presented informative, thought-provoking slides and responded to questions from the SRA audience with unique perspectives from their extensive experience with complex interdisciplinary/transdisciplinary modeling that build discrete scenarios to support decisions about tough tradeoffs. A brief summary of the dialogue is provided after the video.

Brief Summary of Responses to Questions from SRA Audience

The panelists responded with complementary perspectives to many questions, particularly about the need for clarity (transparency in risk jargon) and consistency in Risk Communication when new information about the virus and the pandemic is expanding each day from many sources around the world. Both panelists agreed that one key to effective Risk Communication is that communicating absolute certainties is a grave mistake. Both the virus and public perceptions of the risk of illness/death are continuously evolving, and the media has sometimes blurred the emerging scientific evidence, contributing to escalation of local outbreaks by reporting premature findings with greater confidence than deserved at the time.

Neither panelist was aware of development of a model to date that broadly integrates risk assessment and decision analysis (e.g., systemic risk, simultaneously modeling risk and recovery for public health, security, social, and economic/financial sectors), with feasible scenario modeling of alternative response strategies or policies. Such modeling is very difficult to design and test in this climate of ‘deep uncertainty’ with so many factors and dependencies to continuously update and model across disciplines and around the world. Science seems to progresses incrementally, with fine tuning of ideas and theoretical models based on peer review and additional data and deliberation amongst the professional community. However, when faced with ‘deep uncertainty‘ due to conflicting models and preliminary or ambiguous data, the very strong human temptation is to prematurely select the model predicting the most desirable outcomes rather than to support deliberative processes that provide more reliable decision support. The speakers offered these dramatically different situations to inform future risk-based decision analysis.

In the UK, these factors derailed Risk Communication efforts as described by Prof. Monitbeller. Major problem was the premature selection of a novel theoretical model, perhaps a ‘best-case’ model predicting that the outbreak was waning and not the serious public health problem predicted by the competing model that predicting undesirable outcomes. The decision makers did not seem to understand at the time that the ‘best-case’ model that predicted the desired results was based on preliminary data that oversimplified and mischaracterized real life and death scenarios. This selection bias and faulty risk analysis in the face of ‘deep uncertainties’ likely led to continued escalation of transmission to new cases in the UK.

In Germany, Risk Communication was exceptional as described by Dr. Schweizer, with daily press conferences including both political leaders and scientists who were trained to share evidence as knowledge expanded, with care to openly and fairly represent uncertainties. Daily press conferences proved an essential service to stopping the outbreak in Germany, communicating actual and perceived risks and uncertainties clearly (transparently) with the public and continuously updating and revising what they thought they knew the day as knowledge expanded. Dr. Schweizer also described a ‘miracle’: the Robert Koch Institut had test kits prepared for broad scale, comprehensive testing and research BEFORE the outbreak hit Germany. The Chancellor also clearly communicated that strict countermeasures were needed and built trust, emphasizing that social distancing was a common societal responsibility that depended on compliance of each and every citizen to stop disease transmission. The public trusted and followed this careful Risk Communication and contributed to the successful end of disease transmission in Germany.

To sum up, why did these esteemed risk analysts spend nearly an hour in dialogue about uncertainty in the SRA webinar? Because uncertainty must be framed for all stakeholders to understand, based on data (evidence) and models (describing and extrapolating from the evidence) in order to support reasoned deliberative risk management and evidence-based decision support for selecting, implementing, and evaluating alternative strategies to stop the pandemic.

For unique perspective from SRA Past President Rae Zimmerman (NYU Wanger) on her experience as a risk analyst in the US epicenter of the pandemic, click on the link to the first Let’s Talk Risk podcast of her 30-minute conversation with current SRA President Seth Guikema. Professor Zimmerman also mentioned successes in Germany’s response to the pandemic and the urgency for applying deep knowledge of the principles of risk analysis, particularly Risk Communication and managing competing risks (e.g., personal and societal) and conflicting priorities as the pandemic continues. She notes that NY has survived many catastrophes and disasters in the past, but none quite as broad or disruptive of so many systems, including public health, economics, education, social equity, transportation) for so long. Her third Big Research Question addressed Risk Communication, how to encourage people under stress to make positive behavioral adjustments to adapt to our new reality. Professor Zimmerman reminded us to celebrate our first responders and health care professionals during this crisis, as NY City residents do (#ClapBecauseWeCare) and Italians do, singing from their rooftops and balconies.

BOTTOM LINE

Have hope, but play it smart by following guidance from WHO (DO THE FIVE, below), CDC (Use of Cloth Face Coverings to Help Slow the Spread of COVID-19), and other local public health organizations. Even though WHO recommends 3 meters for social distancing and CDC recommends 6 feet, social distancing and quarantine are effective measures to reduce the likelihood of both exposure and illness, particularly severe illness.

Feel free to ask questions in the Comment section below and I will respond within a few days. My next blog will be posted after the second episode of the SRA biweekly COVID Conversations on Risk webinar series on April 23rd. The current state of the pandemic as of April 9th is illustrated below from the WHO Situation Report 80 (Figure 1).

Addendum: List of SRA Specialty Groups, Contacts, and Websites

Applied Risk Management John Lathrop Visit our website

Decision Analysis and Risk Christian Beaudrie Visit our website

Dose Response Weihsueh Chiu Visit our website 

Ecological Risk Assessment Amanda Bailey Visit our website 

Economics and Benefits Analysis Travis Minor Visit our website

Emerging Nanoscale Materials James Ede, Debra Kaden  Visit our website 

Engineering and Infrastructure Roshanak Nateghi Visit our website 

Exposure Assessment Amina Wilkins, Chris Greene Visit our website 

Foundational Issues in Risk Analysis Seth Guikema,Roger Flage Visit our website 

Microbial Risk Analysis Regis Pouillot Visit our website 

Occupational Health and Safety Scott Dotson Visit our website 

Resilience Analysis Igor Linkov, Terje Aven Visit our website 

Risk and Development Vanessa Schweizer Visit our website 

Risk Communication Laura Rickard Visit our website 

Risk Policy and Law Dominic Balog-Way Visit our website 

Security and Defense Kenneth Crowther Visit our website

Consider evidence on the COVID-19 pandemic and perspective of a microbial risk assessor that points to decreasing fatality ratios with earlier case and contact identification, isolation, and treatment as noted by the WHO.

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is clearly impacting the lives of people all around the world. The World Health Organization (WHO) reports estimated confirmed cases world-wide totaling 193,475 as of March 18th, including 7,864 deaths (estimated overall crude fatality ratio for the pandemic approximately 4%). I commend those who are working to limit spread of this novel virus and care for those who are ill and recovering. I decided to post this summary of what I have learned in five days of investigation of research on the pandemic and SARS viruses today out of concern for those fearful of becoming ill and/or infecting others. My timeline and learnings are summarized below, with some answers to tough questions.

ON MARCH 12TH, Professor Seth Guikema, current President of the Society for Risk Analysis (SRA), organized a webinar that featured an expert panel who provided Risk Analysis Perspectives on COVID-19 Outbreak. Click below to view the 1-hour podcast from this webinar.

Wuhan, the capital city of Hubei Province and the most populous city in central China (>11 million), suffered a local outbreak of pneumonia identified last December that was associated with presence at the Huanan Seafood Wholesale Market. Although no animal source was identified, the virus was isolated from lung fluid samples of early cases, sequenced, and identified as a novel Coronavirus (CoV),named SARS-CoV-2. The virus spread rapidly from the epicenter in Wuhan throughout mainland China and around the world. However, the World Health Organization (WHO, 2020) reported that disease severity was highest where the outbreak started, in the epicenter at Wuhan. The crude fatality ratio for Wuhan was estimated at 5.8% as of February 24, versus 0.7 in other areas of China. Also, fatalities were highest early in the outbreak (17.3% crude fatality ratio prior to management interventions and when the local care facilities were overwhelmed, WHO Figure 4 below. Mortality was demonstrated to increase with age and with underlying medical conditions such as cardiovascular disease and chronic respiratory disease (7.6% to 13.2 %). Severity was highest among those 80 year of age or older (21.9%). WHO attributes earlier case and contact identification, isolation, and treatment as major factors contributing to consistently decreasing fatality ratios, a promising result for other countries managing the pandemic, and even severe cases recovered or were upgraded to milder disease classifications in the period of reporting.

Wuhan represented ineffective risk management, the worst-case scenario to date. Risk managers in China delayed responding to contain viral spread from the first confirmed pneumonia case in early December, 2019, until January 23rd when quarantines were enforced. By that time, more than 55,000 cases were confirmed, and a daily rate of spread was reportedly 140 new cases per day, concentrated in Wuhan but some in each Province of China. In January, cases were being confirmed around the world, predominantly associated with travel and contact with cases. Last week, Wuhan was designated a ‘high-risk area’. However, reports are consistent with decline of the outbreak in other areas considered ‘medium-’ or ‘low-risk’. Restrictions on quarantine are being lifted as the daily case rates drop. Overall, Wuhan and Hubei Province accounted for 96% of deaths in China (3111/3230 as of March 17th), while many regions reported less than 10 or no deaths. WHO (2020) emphasized to the public that the dramatic decline of the outbreak in China demonstrates that pandemic risk can be managed and that the vast majority of infected people will recover with proper precautions and case management.

The SRA webinar speakers described Singapore as representing a ‘best-case scenario’ of effective risk management where prompt response and high compliance with social distancing and quarantine instructions limited viral spread (only 266 cases) and prevented severe fatal complications (no fatalities reported to date.

ON MARCH 14TH, I accessed webpages for Health Canada and CDC for information about the pandemic in North America and updates on risk communications and case numbers. I was particularly impressed with the series of infographics provided by Health Canada. Their risk communication ‘About Corona Virus Disease (COVID-19)’ began by informing readers that ‘human corona viruses are common and typically associated with mild illnesses, similar to the common cold’. The ‘Know the Facts’ communication presents the symptoms (fever, cough, and difficulty breathing) with advice to minimize transmission. CDC also provided resources for communicating with the public about the virus and the pandemic. The ‘Share the Facts about COVID-19’ poster cautions that for most people, the risk of serious illness is thought to be low. Learn more about the virus, the disease, and protecting yourself and your neighbors by opening these attachments and sharing them with others.

ON MARCH 15TH, I was encouraged that my small local newspaper, the Syracuse Post Standard, included a 10-page special section on the pandemic. On the cover was a full page image of a masked person with the headlines: ‘PANICKED ABOUT CORONA VIRUS? STOP. TAKE OFF THE MASK. READ THIS.’ WHO and the local writer and editor agreed that masks are for sick people with symptoms of pneumonia (fever, cough, shortness of breath) to keep from spreading the virus, not for the worried well to prevent exposure to the virus that does not persist long in the air outside of droplets from the coughs and sneezes of symptomatic people near you. Social distancing (keeping 6 feet away from others) ensures that any droplets that could contain virus will not be present in your breathing zone. Much of the 10 pages of content in the local paper was consistent with the WHO report and its recommendations.

ON MARCH 17TH, I found a number of repositories of advice, research, and data on the pandemic that are freely accessible to the public.

One site is the COVID-19 Interactive Map prepared by the Johns Hopkins Corona Virus Resource Center. From this site, the table to the left reflects information for the 6 states in the US with the highest numbers of cases, as of March 17th. An additional 11 states had reported a single death in this time period but are not listed here. These data clearly demonstrate that the virus is spreading in the US, but thankfully, fatality rates in those states where fatalities occurred have not approached those of Wuhan. The elder care facilities in WA state represent the major source of fatalities in the US.

WHO Cornonavirus Disease (COVID) Outbreak Situation Dashboard for updates on cases, other information on tabs marked Your Questions Answered, Mythbusters.

NIH research on corona viruses and the pandemic

Free open resource for researchers, CORD-19 Open Research Dataset on corona virus studies, including WHO database publications. I downloaded metadata data.

ON MARCH 18TH, CDC published two reports on preliminary data for the COVID-19 pandemic in the US: disease severity by age group in the US and a report on the outbreak in the long-term care facility in WA state.

The good news from the first report is, of the 4,226 cases reported in the US since February 12th, 88% have NOT required hospitalization.

The bad news is, 31% of cases to date, 45% of the 508 hospitalized, 53% of the 121 admitted to the ICU, and 80% of deaths were older than 65 years of age. Consistent with WHO reports from China, risk of more severe outcomes increases with age as depicted in the figure below.

The second report on the 129 cases and 23 deaths among those exposed in this time period at a long-term care facility (81 of 130 residents, 34 of 170 staff members, and 14 visitors), illustrates a sobering fact: combining risk factors of a sensitive age group (>80 years old) and chronic underlying medical conditions increases the risk for severe and fatal illness. More than a quarter of those ill were also suffering from one or more of the pre-existing chronic underlying illnesses (hypertension, cardiac disease, renal disease, diabetes mellitus, obesity, or pulmonary disease as co-morbidities). Further, ineffective controls and staff members working at multiple facilities contributed to spread of the outbreak within and between facilities.

FEAR NOT TESTING POSITIVE

As data accumulate in the US from testing of nasal swabs for the presence of SARS-CoV-2, some perspective on the disease mechanism will be helpful to consider, in addition to data from WHO and CDC summarized above. The caution is that just the presence of a virus in a nasal swab sample, without symptoms of pneumonia, means only that you have been exposed, not necessarily that you are infected or that you will become ill. The points below indicate how healthy people are likely to fight off infection even if exposed to the virus.

A great deal of information is known about the initial mechanisms that corona viruses use to infect host cells, including breaking studies on binding of the pandemic virus SARS-CoV-2 to host cells. Very recently, multiple studies determined that the same receptors on human cell membranes are the targets for adherence/tethering and subsequent tighter high affinity binding of both the pandemic virus and related SARS viral strains. The CDC image below includes labels for key surface components of the virus that are essential to its ability to infect human cells, particularly the clove-shaped S glycoprotein highlighted in red.

The studies below are geared to the scientific community, but I provide links to these studies for those who would like more details about the intricate mechanisms and the sophisticated study designs that so quickly advanced knowledge about the pandemic virus.

• Chen et al., 2020 (Structure Analysis of the Receptor Binding of 2019-nCoV)

• Cao et al., 2020 (Comparative Genetic Analysis of the Novel Coronavirus (2019-nCoV/SARS-CoV-2) Receptor ACE2 in Different Populations)

• Guo et al., 2020 (The Origin, Transmission and Clinical Therapies on Coronavirus Disease 2019 (COVID-19) Outbreak – An Update on the Status)

• Quing et al., 2020 (Distinct Roles for Sialoside and Protein Receptors in Coronavirus Infection)

• Song et al., 2019 (From SARS to MERS, Thrusting Coronaviruses into the Spotlight)

• Lim et al., 2016 (Human Coronaviruses: A Review of Virus–Host Interactions)

Two relevant finding from these studies are of interest for the pubic. First, identifying compounds that interfere with binding of the virus (e.g., antibodies from a recovered person) is a promising strategy for designing vaccines and therapeutics to prevent future pandemics. Second, the human receptor that tightly binds virus is more highly expressed deep in the lungs (tiny air sacs or alveoli, bronchi, alveolar immune cells) than in the upper respiratory tract. It is unclear if SARS-CoV-2 infects and replicates in host cells of the upper respiratory system, but it certainly does in the deep lung tissues where the damage occurs that could lead to fatal respiratory failure. So, just presence of the virus in the nose only ensures that you’ve been exposed, not that the virus has infected your lungs.

A great desktop resource for a medical microbiologist, Schaechter’s Mechanisms of Microbial Disease, provides additional information about biological protections that limit viral spread in health humans. First, the specialized hairs in the nose (vibrissae) filter and trap particles including viruses from entering the deep lung. Next, cells lining the respiratory tract from the nose to the bronchioles in the deep lung are covered with mucous and cilia that eliminate inhaled microbes, pushing particles up the ‘escalator’ and out of the lungs (technical term, mucocilliary escalator). Anatomical characteristics of the respiratory tract also limit entry of inhaled microbes, but will not be discussed in detail here. For viruses that may make it to the deep lung alveoli, immune defenses await: antibodies, complement, alveolar macrophages that signal other immune cells to assist in removing and killing invading viruses (and bacteria). These immune defenses are also present in the mouth to process any pathogen moved up the mucocilliary escalator from the deep lung.

More recent studies (Voelker and Numata, 2019; Zhao et al., 2019; Lu et al., 2020; Varricchio et al., 2020) document in more detail the mechanisms by which our innate immune systems call on the cellular defenses mentioned above through activity of Toll-like receptors, interferon-induced transmembrane proteins, and phosopholipid to eliminate pathogens including viruses from the respiratory system.

Further, this breaking report (Thevarajan et al., 2020) documented that innate and adaptive immunity was key in recovery of a case exposed in Wuhan who traveled to Australia before illness developed. These cell types and antibodies directed against SARS-CoV-2 were detected in the blood prior to and during recovery for at least 13 days following exposure.

• antibody-secreting cells (ASCs)

• specific T-lymphocytes (activated CD4+ T cells; CD8+ T cells; follicular helper T cells)

• immunoglobulin M (IgM) and IgG antibodies

The patient was discharged after one week of care. Changes over time (kinetics) of the sustained immune response were documented, particularly progressive increases in antibody response (both IgM and IgG) until day 20. Minimal pro-inflammatory cytokines and chemokines were detected, even during symptomatic periods at days 7-9. The authors hypothesize that understanding early adaptive immune responses might correlate with better clinical outcomes and, in the future, enhance recovery rates for severe cases of COVID-19.

Another very recent study (Guo et al., 2020) reported dramatic differences between case severity and blood chemistry and immune responses. Mild cases had normal or slightly decreased counts of white blood cells and platelets (lymphocytopenia). Severe cases had significantly higher counts of key blood components (neutrophils, D-dimer, blood urea, creatinine, interleukins IL-6 and -10, and tumor necrosis factor alpha (TNF)) and lower lymphocyte counts. In addition, ICU patients had more extreme changes in blood (higher IL-2, -7, and -10, granulocyte stimulating factor, interferon gamma induced protein, monocyte chemo-attractant proteins, macrophage inflammatory protein, and TNF) indicative of cytokine storm, septic shock, and metabolic and coagulation disorders.

MICROBIOME EFFECTS

If you know me as a scientist, you know how fascinated I am by the communities of microbes that live in and on us as partners in health: our microbiota.

You may not know that our upper and lower respiratory tracts are NOT STERILE, but have dense and diverse microbes colonizing surfaces. I encourage you to take a look at the abstracts and figures in these studies:

• De Ruter et al., 2020 (Dual and Triple Epithelial Coculture Model Systems with Donor-Derived Microbiota and THP-1 Macrophages to Mimic Host-Microbe Interactions in the Human Sinonasal Cavities)

• Chun et al., 2020 (Integrative Study of the Upper and Lower Airway Microbiome and Transcriptome in Asthma)

• Zhang et al., 2020 (Characterization of Antibiotic Resistance and Host-Microbiome Interactions in the Human Upper Respiratory Tract during Influenza Infection)

• Kumpitsch et al., 2019 (The Microbiome of the Upper Respiratory Tract in Health and Disease)

I am pleased to connect you with Professor Glenn Gibson, Food Microbial Sciences Unit, University of Reading, UK, through his blog Can Probiotics and Prebiotics go Viral?. In the blog, Prof. Gibson cites this double blind, randomized human clinical trial (deVrese et al., 2005) that concluded that ingestion of a specific probiotic product for 3 months shortened common cold episodes by nearly 2 days and reduced the severity of symptoms.

Prof. Gibson’s blog next mentions a more recent systematic review of multiple studies (Hao et al., 2015; Probiotics for Preventing Acute Upper Respiratory Tract Infections) that concluded ‘Probiotics were found to be better than placebo in reducing the number of participants experiencing episodes of acute [upper respiratory tract infections] URTI by about 47% and the duration of an episode of acute URTI by about 1.89 days.’

Also relevant to this conversation are a tremendous number of recent studies that document connections between the gut microbiota and dietary choices on risks of respiratory tract diseases. I highlight these studies below but invite you to contact me for more information.

• Tromp et al., 2020 (Breastfeeding and the Risk of Respiratory Tract Infections after Infancy: The Generation R Study)

• Van der Gaag et al., 2020 (Influence of Dietary Advice Including Green Vegetables, Beef, and Whole Dairy Products on Recurrent Upper Respiratory Tract Infections in Children: A Randomized Controlled Trial)

• Perdijk et al., 2018 (Cow’s Milk and Immune Function in the Respiratory Tract: Potential Mechanisms)

• Shida et al., 2017 (Daily Intake of Fermented Milk with Lactobacillus casei strain Shirota Reduces the Incidence and Duration of Upper Respiratory Tract Infections in Healthy Middle‑Aged Office Workers)

• Loss et al., 2015 (Consumption of Unprocessed Cow’s Milk Protects Infants from Common Respiratory Infections)

BOTTOM LINE

I repeat, fear not. Social distancing and quarantine are well documented to reduce the likelihood of both exposure and illness, particularly severe illness. Even if your nasal swab tests positive for the pandemic virus SARS-CoV-2, early detection and proper care are likely to bring you to full recovery without complications involving severe pulmonary distress. WHO (2020), Figure 6A below illustrates the ‘worst-case’ scenario to date where delayed social distancing and quarantine caused high case numbers (nearly 3,000 per day for about a week at the peak in the second phase of the outbreak) that overwhelmed local resources and contributed to high local fatality rates early in the outbreak expanding from Wuhan.